# Patent

## Title
Multi-input adaptive filter based on combination of sum-modified Laplacian filter indexing and quadtree partitioning

## Abstract

Filtering is applied at a video encoder, and filter information is encoded in the bitstream to enable a video decoder to identify the filtering that was applied at the video encoder. The video decoder receives encoded video data that includes the filter information, decodes the video data, and applies filtering based on the filtering information. In this way, the decoder applies the same filtering that was applied at the encoder. Video can be encoded utilizing multiple filters with Laplacian filter indexing for multiple inputs for coded units partitioned using a quadtree partitioning scheme.

## Background
This application claims the benefit of U.S. Provisional Application No. 61/379,253, filed on Sep. 1, 2010, U.S. Provisional Application No. 61/379,255, filed on Sep. 1, 2010, and U.S. Provisional Application No. 61/487,231, filed on May 17, 2011, the entire contents each of which are incorporated herein by reference.


TECHNICAL FIELD
This disclosure relates to block-based digital video coding used to compress video data and, more particularly, techniques for determining filters for use in the filtering of video blocks.
BACKGROUND
Digital video capabilities can be incorporated into a wide range of devices, including digital televisions, digital direct broadcast systems, wireless communication devices such as radio telephone handsets, wireless broadcast systems, personal digital assistants (PDAs), laptop computers, desktop computers, tablet computers, digital cameras, digital recording devices, video gaming devices, video game consoles, and the like. Digital video devices implement video compression techniques, such as MPEG-2, MPEG-4, or ITU-T H.264/MPEG-4, Part 10, Advanced Video Coding (AVC), to transmit and receive digital video more efficiently. Video compression techniques perform spatial and temporal prediction to reduce or remove redundancy inherent in video sequences. New video standards, such as the High Efficiency Video Coding (HEVC) standard being developed by the “Joint Collaborative Team—Video Coding” (JCTVC), which is a collaboration between MPEG and ITU-T, continue to emerge and evolve. This new HEVC standard is also sometimes referred to as H.265.
Block-based video compression techniques may perform spatial prediction and/or temporal prediction. Intra-coding relies on spatial prediction to reduce or remove spatial redundancy between video blocks within a given unit of coded video, which may comprise a video frame, a slice of a video frame, or the like. In contrast, inter-coding relies on temporal prediction to reduce or remove temporal redundancy between video blocks of successive coded units of a video sequence. For intra-coding, a video encoder performs spatial prediction to compress data based on other data within the same unit of coded video. For inter-coding, the video encoder performs motion estimation and motion compensation to track the movement of corresponding video blocks of two or more adjacent units of coded video.
A coded video block may be represented by prediction information that can be used to create or identify a predictive block, and a residual block of data indicative of differences between the block being coded and the predictive block. In the case of inter-coding, one or more motion vectors are used to identify the predictive block of data from a previous or subsequent coded unit, while in the case of intra-coding, the prediction mode can be used to generate the predictive block based on data within the coded unit associated with the video block being coded. Both intra-coding and inter-coding may define several different prediction modes, which may define different block sizes and/or prediction techniques used in the coding. Additional types of syntax elements may also be included as part of encoded video data in order to control or define the coding techniques or parameters used in the coding process.
After block-based prediction coding, the video encoder may apply transform, quantization and entropy coding processes to further reduce the bit rate associated with communication of a residual block. Transform techniques may comprise discrete cosine transforms (DCTs) or conceptually similar processes, such as wavelet transforms, integer transforms, or other types of transforms. In a discrete cosine transform process, as an example, the transform process converts a set of pixel values into transform coefficients, which may represent the energy of the pixel values in the frequency domain. Quantization is applied to the transform coefficients, and generally involves a process that limits the number of bits associated with any given transform coefficient. Entropy coding comprises one or more processes that collectively compress a sequence of quantized transform coefficients.
Filtering of video blocks may be applied as part of the encoding and decoding loops, or as part of a post-filtering process on reconstructed video blocks. Filtering is commonly used, for example, to reduce blockiness or other artifacts common to block-based video coding. Filter coefficients (sometimes called filter taps) may be defined or selected in order to promote desirable levels of video block filtering that can reduce blockiness and/or improve the video quality in other ways. A set of filter coefficients, for example, may define how filtering is applied along edges of video blocks or other locations within video blocks. Different filter coefficients may cause different levels of filtering with respect to different pixels of the video blocks. Filtering, for example, may smooth or sharpen differences in intensity of adjacent pixel values in order to help eliminate unwanted artifacts.
SUMMARY
This disclosure describes techniques associated with filtering of video data in a video encoding and/or video decoding process. In accordance with this disclosure, filtering is applied at an encoder, and filter information is encoded in the bitstream to enable a decoder to identify the filtering that was applied at the encoder. The decoder receives encoded video data that includes the filter information, decodes the video data, and applies filtering based on the filtering information. In this way, the decoder applies the same filtering that was applied at the encoder.
According to the techniques of this disclosure, video data can be coded in units referred to as coded units (CUs). Coded units can be partitioned into smaller coded units, or sub-units, using a quadtree partitioning scheme. Syntax identifying the quadtree partitioning scheme for a particular coded unit can be transmitted from an encoder to a decoder. Multiple inputs associated with each sub-unit can be filtered during the process of decoding and reconstructing the encoded video data. Syntax in the bitstream received by the decoder can identify the filters used at the encoder for a particular sub-unit. The filter used for a particular input can be selected based on activity-metric filter indexing, where certain values for an activity metric are indexed to specific filters within a set of filters. In cases where the activity metric is determined using a sum-modified Laplacian value, the activity-metric filter indexing is sometimes referred to sum-modified Laplacian indexing or just Laplacian indexing.
Different types of filtering may be applied based on an activity metric determined for the video data. The activity metric may quantify activity associated with one or more blocks of pixels within the video data. The activity metric may comprise a variance metric indicative of pixel variance within a set of pixels. For example, the activity metric may include a sum-modified Laplacian function value, as explained in greater detail below. According to the techniques of this disclosure, a filter unit, such as an adaptive-in loop filter, can be configured to utilize multiple filters for multiple inputs based on sum-modified Laplacian filter indexing. As will be described in more detail below, the multiple inputs described in this disclosure generally refer to intermediate video block data or image data that is produced during the encoding and decoding processes. Multiple inputs can include, for example, a reconstructed block or image (RI), a pre-deblocked reconstructed block or image (pRI), a prediction block or image (PI), and/or a quantized prediction error image (EI). Also, as explained in greater detail below, the filtering techniques of this disclosure can be applied to coded units of various sizes using a quadtree partitioning scheme. By utilizing multiple filters with Laplacian filter indexing for multiple inputs for coded units partitioned using a quadtree partitioning scheme, video coding performance, as measured by one or both of compression rate and reconstructed video quality, might be improved.
A multi-input, multi-filter approach, as contemplated in this disclosure, can result in a large number of filters, and hence a large number of filter coefficients needing to be transferred from an encoder to a decoder. For some filters, however, all the coefficients might be zero. For example, in a 4-input scenario, an encoder may determine that the best image is obtained by only using three of the four inputs. At the decoder, reconstructing an image based on only three out of four inputs can be achieved by applying a filter of all zeros to the fourth input. Accordingly, the use of a filter with all zero coefficients may occur more frequently in multi-input filtering schemes than in single-input filtering schemes. Transmitting a filter of all zeros, however, can require a large number of bits. To reduce the number of coded bits needed to transfer the filter coefficients from encoder to decoder, aspects of the present disclosure include the use of a zero flag, which can be a one-bit syntax element in a header of a frame, slice, largest coded unit, coded unit, or other series of video blocks. If all the coefficients for a particular filter are zero, then the encoder can transmit to the decoder a zero flag set to a first value. Upon receiving a zero flag set to the first value, the decoder can reconstruct the filter without actually receiving data identifying all the zero coefficients from the encoder. If the coefficients for a particular filter include at least one non-zero coefficient, then the encoder can transmit to the decoder a zero flag set to a second value. Upon receiving a zero flag set to the second value, the decoder reconstructs the filter based on coefficients subsequently received from the encoder. Thus, in order to reconstruct a filter, an encoder may only need to transmit filter coefficients to a decoder for those cases where at least one filter coefficient is non-zero.
In one example, a method of coding video data includes applying a first filter from a set of filters to a first input based on an activity metric to generate a first filtered result; applying a second filter to a second input to generate a second filtered result, wherein the second input is different than the first input; and, generating a filtered image based on the first filtered result and the second filtered result.
In another example, a coding device includes a filter unit configured to apply a first filter from a set of filters to a first input based on an activity metric to generate a first filtered result and apply a second filter to a second input to generate a second filtered result, wherein the second input is different than the first input; and, a memory configured to store a filtered image based on the first filtered result and the second filtered result.
In another example, an apparatus includes means for applying a first filter from a set of filters to a first input based on an activity metric to generate a first filtered result; means for applying a second filter to a second input to generate a second filtered result, wherein the second input is different than the first input; and, means for generating a filtered image based on the first filtered result and the second filtered result.
The techniques described in this disclosure may be implemented in hardware, software, firmware, or any combination thereof. If implemented in hardware, an apparatus may be realized as an integrated circuit, a processor, discrete logic, or any combination thereof. If implemented in software, the software may be executed in one or more processors, such as a microprocessor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), or digital signal processor (DSP). The software that executes the techniques may be initially stored in a computer-readable medium and loaded and executed in the processor.
Accordingly, this disclosure also contemplates a non-transitory, computer readable storage medium tangibly storing one or more instructions, which when executed by one or more processors cause the one or more processors to apply a first filter from a set of filters to a first input based on an activity metric to generate a first filtered result; apply a second filter to a second input to generate a second filtered result, wherein the second input is different than the first input; and, generate a filtered image based on the first filtered result and the second filtered result.
The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques described in this disclosure will be apparent from the description and drawings, and from the claims.



BRIEF DESCRIPTION OF DRAWINGS
FIG. 1 is a block diagram illustrating an exemplary video encoding and decoding system.
FIGS. 2A and 2B are conceptual diagrams illustrating an example of quadtree partitioning applied to a largest coding unit (LCU).
FIGS. 2C and 2D are conceptual diagrams illustrating examples of filter maps.
FIG. 3 is a block diagram illustrating an exemplary video encoder consistent with this disclosure.
FIG. 4 is a block diagram illustrating an exemplary video decoder consistent with this disclosure.
FIG. 5 is a conceptual diagram illustrating ranges of values for an activity metric.
FIG. 6 is a block diagram illustrating an exemplary filter unit consistent with this disclosure.
FIG. 7 is a flow diagram illustrating an encoding technique consistent with this disclosure.
FIG. 8 is a flow diagram illustrating a decoding technique consistent with this disclosure.
FIG. 9 is a flow diagram illustrating an encoding technique consistent with this disclosure.
FIG. 10 is a flow diagram illustrating a decoding technique consistent with this disclosure.



DETAILED DESCRIPTION
This disclosure describes techniques associated with filtering of video data in a video encoding and/or video decoding process. In accordance with this disclosure, filtering is applied at an encoder, and filter information is encoded in the bitstream to enable a decoder to identify the filtering that was applied at the encoder. The decoder receives encoded video data that includes the filter information, decodes the video data, and applies filtering based on the filtering information. In this way, the decoder applies the same filtering that was applied at the encoder.
According to the techniques of this disclosure, video data can be coded in units referred to as coded units (CUs). Coded units can be partitioned into smaller coded units, or sub-units, using a quadtree partitioning scheme. Syntax identifying the quadtree partitioning scheme for a particular coded unit can be transmitted from an encoder to a decoder. Multiple inputs associated with each sub-unit can be filtered during the process of decoding and reconstructing the encoded video data. Syntax in the bitstream received by the decoder can identify the filters used at the encoder for a particular sub-unit. The filter used for a particular input can be selected based on activity-metric filter indexing, where certain values for an activity metric are indexed to specific filters within a set of filters. In cases where the activity metric is determined using a sum-modified Laplacian value, the activity-metric filter indexing is sometimes referred to sum-modified Laplacian indexing or just Laplacian indexing.
Different types of filtering may be applied based on an activity metric determined for the video data. The activity metric may quantify activity associated with one or more blocks of pixels within the video data. The activity metric may comprise a variance metric indicative of pixel variance within a set of pixels. For example, the activity metric may include a sum-modified Laplacian function value, as explained in greater detail below. According to the techniques of this disclosure, a filter unit, such as an adaptive-in loop filter, can be configured to utilize multiple filters for multiple inputs based on sum-modified Laplacian filter indexing. As will be described in more detail below, the multiple inputs described in this disclosure generally refer to intermediate video block data or image data that is produced during the encoding and decoding processes. Multiple inputs can include, for example, a reconstructed block or image (RI), a pre-deblocked reconstructed block or image (pRI), a prediction block or image (PI), and/or a quantized prediction error image (EI). Also, as explained in greater detail below, the filtering techniques of this disclosure can be applied to coded units of various sizes using a quadtree partitioning scheme. By utilizing multiple filters with Laplacian filter indexing for multiple inputs for coded units partitioned using a quadtree partitioning scheme, video coding performance, as measured by one or both of compression rate and reconstructed video quality, might be improved.
A multi-input, multi-filter approach, as contemplated in this disclosure, can result in a large number of filters, and hence a large number of filter coefficients needing to be transferred from an encoder to a decoder. For some filters, however, all the coefficients might be zero. For example, in a 4-input scenario, an encoder may determine that the best image is obtained by only using three of the four inputs. At the decoder, reconstructing an image based on only three out of four inputs can be achieved by applying a filter of all zeros to the fourth input. Accordingly, the use of a filter with all zero coefficients may occur more frequently in multi-input filtering schemes than in single-input filtering schemes. Transmitting a filter of all zeros, however, can require a large number of bits. For example, in the case of a 9×9 filter where each filter coefficient is transmitted using 5 bits, transmitting all the coefficients of the filter from the encoder to the decoder may take in excess of 400 bits.
To reduce the number of coded bits needed to transfer the filter coefficients from encoder to decoder, aspects of the present disclosure include the use of a zero flag, which can be a one-bit syntax element in a header of a frame, slice, largest coded unit, coded unit, or other series of video blocks. If all the coefficients for a particular filter are zero, then the encoder can transmit to the decoder a zero flag set to a first value. Upon receiving a zero flag set to the first value, the decoder can reconstruct the filter without actually receiving data identifying all the zero coefficients from the encoder. If the coefficients for a particular filter include at least one non-zero coefficient, then the encoder can transmit to the decoder a zero flag set to a second value. Upon receiving a zero flag set to the second value, the decoder reconstructs the filter based on coefficients subsequently received from the encoder. Thus, in order to reconstruct a filter, an encoder may only need to transmit filter coefficients to a decoder for those cases where at least one filter coefficient is non-zero.
The zero flag transmitted by the encoder may, for example, be included in the header of a series of video blocks, such as in a slice header, group-of-pictures header, sequence header, or other header. Although this disclosure, for purposes of explanation, will generally discuss the zero flag as being included in a header, the zero flag may alternatively be included in a footer or other data structure where syntax can be included. A header may include one zero flag per filter per input. As an example, assume fm(l, n) equals a filter coefficient for the n-th coefficient, of the l-th filter of the m-th input. Assuming, four inputs (i.e. m=0 to 3) and four filters per input (i.e. l=0 to 3), a coded unit might include a total of 16 zero flags, one for each of the 16 filters. If zero_flagm(l)=1, signifying that all coefficients for the l-th filter of the m-th input are equal to zero, then no coefficients need to be sent from the encoder to the decoder for that filter. If zero_flagm(l)=0, signifying that at least one coefficient of the l-th filter of the m-th input is not equal to zero, then additional data identifying coefficients for the l-th filter of the m-th input are transmitted from the encoder to the decoder. As will be described in more detail below, the additional data may include actual values for some or all of the filter coefficients or may include information such as difference information that allows the decoder to reconstruct the filters based on a combination of the additional data and other information already known to the decoder.
Although the techniques of this disclosure will generally be described in reference to in-loop filtering, the techniques may be applied to in-loop filtering, post-loop filtering, and other filtering schemes such as switched filtering. In-loop filtering refers to filtering in which the filtered data is part of the encoding and decoding loops such that filtered data is used for predictive intra- or inter-coding. Post-loop filtering refers to filtering that is applied to reconstructed video data after the encoding loop. With post filtering, the unfiltered data is used for predictive intra- or inter-coding. The techniques of this disclosure are not limited to in-loop filtering or post filtering, and may apply to a wide range of filtering applied during video coding.
In this disclosure, the term “coding” refers to encoding or decoding. Similarly, the term “coder” generally refers to any video encoder, video decoder, or combined encoder/decoder (codec). Accordingly, the term “coder” is used herein to refer to a specialized computer device or apparatus that performs video encoding or video decoding.
Additionally, in this disclosure, the term “filter” generally refers to a set of filter coefficients. For example, a 3×3 filter is defined by a set of 9 filter coefficients, a 5×5 filter is defined by a set of 25 filter coefficients, and so on. Therefore, encoding a filter generally refers to encoding information in the bitstream that will enable a decoder to determine or reconstruct the set of filter coefficients. While encoding a filter may include directly encoding a full set of filter coefficients, it may also include directly encoding only a partial set of filter coefficients or encoding no filter coefficients at all but rather encoding information that enables a decoder to reconstruct filter coefficients based on other information known or attainable to the decoder. For example, an encoder can encode information describing how to alter a set of existing filter coefficients to create a new set of filter coefficients.
The term “set of filters” generally refers to a group of more than one filter. For example, a set of 2 3×3 filters, could include a first set of 9 filter coefficients and a second set of 9 filter coefficients. According to techniques described in this disclosure, for a series of video blocks, such as a frame, slice, or largest coding unit, information identifying sets of filters are transmitted from the encoder to the decoder in a header for the series of the video blocks. Each filter of the set of filters may have a corresponding zero flag in the header to indicate whether the filter contains all zero coefficients or contains at least one non-zero coefficient.
FIG. 1 is a block diagram illustrating an exemplary video encoding and decoding system 110 that may implement techniques of this disclosure. As shown in FIG. 1, system 110 includes a source device 112 that transmits encoded video data to a destination device 116 via a communication channel 115. Source device 112 and destination device 116 may comprise any of a wide range of devices. In some cases, source device 112 and destination device 116 may comprise wireless communication device handsets, such as so-called cellular or satellite radiotelephones. The techniques of this disclosure, however, which apply more generally to filtering of video data, are not necessarily limited to wireless applications or settings, and may be applied to non-wireless devices including video encoding and/or decoding capabilities.
In the example of FIG. 1, source device 112 includes a video source 120, a video encoder 122, a modulator/demodulator (modem) 123 and a transmitter 124. Destination device 116 includes a receiver 126, a modem 127, a video decoder 128, and a display device 130. In accordance with this disclosure, video encoder 122 of source device 112 may be configured to select one or more sets of filter coefficients for multiple inputs in a video block filtering process and then encode the selected one or more sets of filter coefficients. Specific filters from the one or more sets of filter coefficients may be selected based on an activity metric for one more inputs, and the filter coefficients may be used to filter the one or more inputs. The filtering techniques of this disclosure are generally compatible with any techniques for coding or signaling filter coefficients from an encoder to a decoder.
According to the techniques of this disclosure, video encoder 122 can transmit to video decoder 128 one or more sets of filter coefficients for a frame or slice. For the frame or slice, video encoder 122 may, for example, transmit one set of filters to be used with all inputs, or may transmit multiple sets of filters to be used with multiple inputs (one set per input, for example). Each video block or coded unit within that frame or slice can then contain additional syntax to identify which filter or filters of the set of the filters is to be used for each input of that video block, or which filter or filters of the set of the filters is to be used can be determined based on an activity metric associated with one or more of the inputs.
More specifically, video encoder 122 of source device 112 may select one or more sets of filters for a frame or slice, apply filters from the set(s) to inputs associated with coded units of the slice or frame during the encoding process, and then encode the sets of filters (i.e. sets of filter coefficients) for communication to video decoder 128 of destination device 116. Video encoder 122 may determine an activity metric associated with inputs of coded units coded in order to select which filter(s) from the set(s) of filters to use with that particular coded unit. On the decoder side, video decoder 128 of destination device 116 may also determine the activity metric for one or more inputs associated with the coded unit so that video decoder 128 can determine which filter(s) from the set(s) of filters to apply to the pixel data, or in some instances, video decoder 128 may determine the filter coefficients directly from filter information received in the bitstream syntax. Video decoder 128 may decode the filter coefficients based on direct decoding or predictive decoding depending upon how the filter coefficients were encoded, which may be signaled as part of the bitstream syntax. Additionally, the bitstream may include a zero flag for each filter to indicate whether a filter has non-zero filter coefficients. If the zero flag indicates the filter does not have any non-zero coefficients, then decoder 128 can reconstruct the filter of all zero coefficients without receiving further syntax from source device 112. The illustrated system 110 of FIG. 1 is merely exemplary. The filtering techniques of this disclosure may be performed by any encoding or decoding devices. Source device 112 and destination device 116 are merely examples of coding devices that can support such techniques.
Video encoder 122 of source device 112 may encode video data received from video source 120 using the techniques of this disclosure. Video source 120 may comprise a video capture device, such as a video camera, a video archive containing previously captured video, or a video feed from a video content provider. As a further alternative, video source 120 may generate computer graphics-based data as the source video, or a combination of live video, archived video, and computer-generated video. In some cases, if video source 120 is a video camera, source device 112 and destination device 116 may form so-called camera phones or video phones. In each case, the captured, pre-captured or computer-generated video may be encoded by video encoder 122.
Once the video data is encoded by video encoder 122, the encoded video information may then be modulated by modem 123 according to a communication standard, e.g., such as code division multiple access (CDMA) or another communication standard or technique, and transmitted to destination device 116 via transmitter 124. Modem 123 may include various mixers, filters, amplifiers or other components designed for signal modulation. Transmitter 124 may include circuits designed for transmitting data, including amplifiers, filters, and one or more antennas.
Receiver 126 of destination device 116 receives information over channel 115, and modem 127 demodulates the information. The video decoding process performed by video decoder 128 may include filtering, e.g., as part of the in-loop decoding or as a post filtering step following the decoding loop. Either way, the set of filters applied by video decoder 128 for a particular slice or frame may be decoded using the techniques of this disclosure. If for example a zero flag indicates a filter includes non-zero coefficients and predictive coding is used for the filter coefficients, similarities between different filter coefficients may be exploited to reduce the amount of information conveyed over channel 115. In particular, a filter (i.e. a set of the filter coefficients) can be predictively coded as difference values relative to another set of the filter coefficients associated with a different filter. The different filter may, for example, be associated with a different slice or frame. In such a case, video decoder 128 might receive an encoded bitstream comprising video blocks and filter information that identifies the different frame or slice with which the different filter is associated filter. The filter information also includes difference values that define the current filter relative to the filter of the different coded unit. In particular, the difference values may comprise filter coefficient difference values that define filter coefficients for the current filter relative to filter coefficients of a different filter used for a different coded unit.
Video decoder 128 decodes the video blocks, generates the filter coefficients, and filters the decoded video blocks based on the generated filter coefficients. The decoded and filtered video blocks can be assembled into video frames to form decoded video data. Display device 128 displays the decoded video data to a user, and may comprise any of a variety of display devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), a plasma display, an organic light emitting diode (OLED) display, or another type of display device.
Communication channel 115 may comprise any wireless or wired communication medium, such as a radio frequency (RF) spectrum or one or more physical transmission lines, or any combination of wireless and wired media. Communication channel 115 may form part of a packet-based network, such as a local area network, a wide-area network, or a global network such as the Internet. Communication channel 115 generally represents any suitable communication medium, or collection of different communication media, for transmitting video data from source device 112 to destination device 116.
Video encoder 122 and video decoder 128 may operate according to a video compression standard such as the ITU-T H.264 standard, alternatively referred to as MPEG-4, Part 10, Advanced Video Coding (AVC), which will be used in parts of this disclosure for purposes of explanation. However, many of the techniques of this disclosure may be readily applied to any of a variety of other video coding standards, including the newly emerging HEVC standard. Generally, any standard that allows for filtering at the encoder and decoder may benefit from various aspects of the teaching of this disclosure.
Although not shown in FIG. 1, in some aspects, video encoder 122 and video decoder 128 may each be integrated with an audio encoder and decoder, and may include appropriate MUX-DEMUX units, or other hardware and software, to handle encoding of both audio and video in a common data stream or separate data streams. If applicable, MUX-DEMUX units may conform to the ITU H.223 multiplexer protocol, or other protocols such as the user datagram protocol (UDP).
Video encoder 122 and video decoder 128 each may be implemented as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic, software, hardware, firmware or any combinations thereof. Each of video encoder 122 and video decoder 128 may be included in one or more encoders or decoders, either of which may be integrated as part of a combined encoder/decoder (CODEC) in a respective mobile device, subscriber device, broadcast device, server, or the like.
In some cases, devices 112, 116 may operate in a substantially symmetrical manner. For example, each of devices 112, 116 may include video encoding and decoding components. Hence, system 110 may support one-way or two-way video transmission between video devices 112, 116, e.g., for video streaming, video playback, video broadcasting, or video telephony.
During the encoding process, video encoder 122 may execute a number of coding techniques or steps. In general, video encoder 122 operates on video blocks within individual video frames in order to encode the video data. In one example, a video block may correspond to a macroblock or a partition of a macroblock. Macroblocks are one type of video block defined by the ITU H.264 standard and other standards. Macroblocks typically refer to 16×16 blocks of data, although the term is also sometimes used generically to refer to any video block of N×N size. The ITU-T H.264 standard supports intra prediction in various block sizes, such as 16×16, 8×8, or 4×4 for luma components, and 8×8 for chroma components, as well as inter prediction in various block sizes, such as 16×16, 16×8, 8×16, 8×8, 8×4, 4×8 and 4×4 for luma components and corresponding scaled sizes for chroma components. In this disclosure, “N×N” refers to the pixel dimensions of the block in terms of vertical and horizontal dimensions, e.g., 16×16 pixels. In general, a 16×16 block will have 16 pixels in a vertical direction and 16 pixels in a horizontal direction. Likewise, an N×N block generally has N pixels in a vertical direction and N pixels in a horizontal direction, where N represents a positive integer value. The pixels in a block may be arranged in rows and columns.
The emerging HEVC standard defines new terms for video blocks. In particular, video blocks (or partitions thereof) may be referred to as “coded units” (or CUs). With the HEVC standard, largest coded units (LCUs) may be divided into smaller and CUs according to a quadtree partitioning scheme, and the different CUs that are defined in the scheme may be further partitioned into so-called prediction units (PUs). The LCUs, CUs, and PUs are all video blocks within the meaning of this disclosure. Other types of video blocks may also be used, consistent with the HEVC standard or other video coding standards. Thus, the phrase “video blocks” refers to any size of video block. Separate CUs may be included for luma components and scaled sizes for chroma components for a given pixel, although other color spaces could also be used.
Video blocks may have fixed or varying sizes, and may differ in size according to a specified coding standard. Each video frame may include a plurality of slices. Each slice may include a plurality of video blocks, which may be arranged into partitions, also referred to as sub-blocks. In accordance with the quadtree partitioning scheme referenced above and described in more detail below, an N/2×N/2 first CU may comprise a sub-block of an N×N LCU, an N/4×N/4 second CU may also comprise a sub-block of the first CU. An N/8×N/8 PU may comprise a sub-block of the second CU. Similarly, as a further example, block sizes that are less than 16×16 may be referred to as partitions of a 16×16 video block or as sub-blocks of the 16×16 video block. Likewise, for an N×N block, block sizes less than N×N may be referred to as partitions or sub-blocks of the N×N block. Video blocks may comprise blocks of pixel data in the pixel domain, or blocks of transform coefficients in the transform domain, e.g., following application of a transform such as a discrete cosine transform (DCT), an integer transform, a wavelet transform, or a conceptually similar transform to the residual video block data representing pixel differences between coded video blocks and predictive video blocks. In some cases, a video block may comprise blocks of quantized transform coefficients in the transform domain.
Syntax data within a bitstream may define an LCU for a frame or a slice, which is a largest coding unit in terms of the number of pixels for that frame or slice. In general, an LCU or CU has a similar purpose to a macroblock coded according to H.264, except that LCUs and CUs do not have a specific size distinction. Instead, an LCU size can be defined on a frame-by-frame or slice-by-slice basis, and an LCU be split into CUs. In general, references in this disclosure to a CU may refer to a largest coded unit of a picture or a sub-CU of an LCU. An LCU may be split into sub-CUs, and each sub-CU may be split into sub-CUs. Syntax data for a bitstream may define a maximum number of times an LCU may be split, referred to as CU depth. Accordingly, a bitstream may also define a smallest coding unit (SCU). This disclosure also uses the terms “block” and “video block” to refer to any of an LCU, CU, PU, SCU, or TU.
As introduced above, an LCU may be associated with a quadtree data structure. In general, a quadtree data structure includes one node per CU, where a root node corresponds to the LCU. If a CU is split into four sub-CUs, the node corresponding to the CU includes four leaf nodes, each of which corresponds to one of the sub-CUs. Each node of the quadtree data structure may provide syntax data for the corresponding CU. For example, a node in the quadtree may include a split flag, indicating whether the CU corresponding to the node is split into sub-CUs. Syntax elements for a CU may be defined recursively, and may depend on whether the CU is split into sub-CUs.
A CU that is not split may include one or more prediction units (PUs). In general, a PU represents all or a portion of the corresponding CU, and includes data for retrieving a reference sample for the PU. For example, when the PU is intra-mode encoded, the PU may include data describing an intra-prediction mode for the PU. As another example, when the PU is inter-mode encoded, the PU may include data defining a motion vector for the PU. The data defining the motion vector may describe, for example, a horizontal component of the motion vector, a vertical component of the motion vector, a resolution for the motion vector (e.g., one-quarter pixel precision or one-eighth pixel precision), a reference frame to which the motion vector points, and/or a reference list (e.g., list 0 or list 1) for the motion vector. Data for the CU defining the PU(s) may also describe, for example, partitioning of the CU into one or more PUs. Partitioning modes may differ between whether the CU is uncoded, intra-prediction mode encoded, or inter-prediction mode encoded.
A CU having one or more PUs may also include one or more transform units (TUs). Following prediction using a PU, a video encoder may calculate a residual value for the portion of the CU corresponding to the PU. The residual value may be transformed, quantized, and scanned. A TU is not necessarily limited to the size of a PU. Thus, TUs may be larger or smaller than corresponding PUs for the same CU. In some examples, the maximum size of a TU may be the size of the corresponding CU. The TUs may comprise the data structures that include the residual transform coefficients associated with a given CU.
FIGS. 2A and 2B are conceptual diagrams illustrating an example quadtree 250 and a corresponding largest coding unit 272. FIG. 2A depicts an example quadtree 250, which includes nodes arranged in a hierarchical fashion. Each node in a quadtree, such as quadtree 250, may be a leaf node with no children, or have four child nodes. In the example of FIG. 2A, quadtree 250 includes root node 252. Root node 252 has four child nodes, including leaf nodes 256A-256C (leaf nodes 256) and node 254. Because node 254 is not a leaf node, node 254 includes four child nodes, which in this example, are leaf nodes 258A-258D (leaf nodes 258).
Quadtree 250 may include data describing characteristics of a corresponding largest coding unit (LCU), such as LCU 272 in this example. For example, quadtree 250, by its structure, may describe splitting of the LCU into sub-CUs. Assume that LCU 272 has a size of 2N×2N. LCU 272, in this example, has four sub-CUs 276A-276C (sub-CUs 276) and 274, each of size N×N. Sub-CU 274 is further split into four sub-CUs 278A-278D (sub-CUs 278), each of size N/2×N/2. The structure of quadtree 250 corresponds to the splitting of LCU 272, in this example. That is, root node 252 corresponds to LCU 272, leaf nodes 256 correspond to sub-CUs 276, node 254 corresponds to sub-CU 274, and leaf nodes 258 correspond to sub-CUs 278.
Data for nodes of quadtree 250 may describe whether the CU corresponding to the node is split. If the CU is split, four additional nodes may be present in quadtree 250. In some examples, a node of a quadtree may be implemented similar to the following pseudocode:















quadtree_node {









boolean split_flag(1);



// signaling data



if (split_flag) {









quadtree_node child1;



quadtree_node child2;



quadtree_node child3;



quadtree_node child4;









}









}










The split_flag value may be a one-bit value representative of whether the CU corresponding to the current node is split. If the CU is not split, the split_flag value may be ‘0’, while if the CU is split, the split_flag value may be ‘1’. With respect to the example of quadtree 250, an array of split flag values may be 101000000.

In some examples, each of sub-CUs 276 and sub-CUs 278 may be intra-prediction encoded using the same intra-prediction mode. Accordingly, video encoder 122 may provide an indication of the intra-prediction mode in root node 252. Moreover, certain sizes of sub-CUs may have multiple possible transforms for a particular intra-prediction mode. In accordance with the techniques of this disclosure, video encoder 122 may provide an indication of the transform to use for such sub-CUs in root node 252. For example, sub-CUs of size N/2×N/2 may have multiple possible transforms available. Video encoder 122 may signal the transform to use in root node 252. Accordingly, video decoder 128 may determine the transform to apply to sub-CUs 278 based on the intra-prediction mode signaled in root node 252 and the transform signaled in root node 252.
As such, video encoder 122 need not signal transforms to apply to sub-CUs 276 and sub-CUs 278 in leaf nodes 256 and leaf nodes 258, but may instead simply signal an intra-prediction mode and, in some examples, a transform to apply to certain sizes of sub-CUs, in root node 252, in accordance with the techniques of this disclosure. In this manner, these techniques may reduce the overhead cost of signaling transform functions for each sub-CU of an LCU, such as LCU 272.
In some examples, intra-prediction modes for sub-CUs 276 and/or sub-CUs 278 may be different than intra-prediction modes for LCU 272. Video encoder 122 and video decoder 128 may be configured with functions that map an intra-prediction mode signaled at root node 252 to an available intra-prediction mode for sub-CUs 276 and/or sub-CUs 278. The function may provide a many-to-one mapping of intra-prediction modes available for LCU 272 to intra-prediction modes for sub-CUs 276 and/or sub-CUs 278.
A slice may be divided into video blocks (or LCUs) and each video block may be partitioned according to the quadtree structure described in relation to FIGS. 2A-B. Additionally, as shown in FIG. 2C, the quadtree sub-blocks indicated by “ON” may be filtered by loop filters described herein, while quadtree sub-blocks indicated by “OFF” may not be filtered. The decision of whether or not to filter a given block or sub-block may be determined at the encoder by comparing the filtered result and the non-filtered result relative to the original block being coded. FIG. 2D is a decision tree representing partitioning decisions that results in the quadtree partitioning shown in FIG. 2C.
In particular, FIG. 2C may represent a relatively large video block that is partitioned according to a quadtree portioning scheme into smaller video blocks of varying sizes. Each video block is labelled (on or off) in FIG. 2C, to illustrate whether filtering should be applied or avoided for that video block. Video encoder 122 may define this filter map by comparing filtered and unfiltered versions of each video block to the original video block being coded.
Again, FIG. 2D is a decision tree corresponding to partitioning decisions that result in the quadtree partitioning shown in FIG. 2C. In FIG. 2D, each circle may correspond to a CU. If the circle includes a “1” flag, then that CU is further partitioned into four more CUs, but if the circle includes a “0” flag, then that CU is not partitioned any further. Each circle (e.g., corresponding to CUs) also includes an associated triangle. If the flag in the triangle for a given CU is set to 1, then filtering is turned “ON” for that CU, but if the flag in the triangle for a given CU is set to 0, then filtering is turned off In this manner, FIGS. 2C and 2D may be individually or collectively viewed as a filter map that can be generated at an encoder and communicated to a decoder at least once per slice of encoded video data in order to communicate the level of quadtree partitioning for a given video block (e.g., an LCU) whether or not to apply filtering to each partitioned video block (e.g., each CU within the LCU).
Smaller video blocks can provide better resolution, and may be used for locations of a video frame that include high levels of detail. Larger video blocks can provide greater coding efficiency, and may be used for locations of a video frame that include a low level of detail. A slice may be considered to be a plurality of video blocks and/or sub-blocks. Each slice may be an independently decodable series of video blocks of a video frame. Alternatively, frames themselves may be decodable series of video blocks, or other portions of a frame may be defined as decodable series of video blocks. The term “series of video blocks” may refer to any independently decodable portion of a video frame such as an entire frame, a slice of a frame, a group of pictures (GOP) also referred to as a sequence, or another independently decodable unit defined according to applicable coding techniques. Aspects of this invention might be described in reference to frames or slices, but such references are merely exemplary. It should be understood that generally any series of video blocks may be used instead of a frame or a slice.
Syntax data may be defined on a per-coded-unit basis such that each coded unit includes associated syntax data. The filter information described herein may be part of such syntax for a coded unit, but might more likely be part of syntax for a series of video blocks, such as a frame, a slice, a GOP, or a sequence of video frames, instead of for a coded unit. The syntax data can indicate the set or sets of filters to be used with coded units of the slice or frame. The syntax may additionally describe other characteristics of the filters (e.g., filter types) that were used to filter the coded units of the slice or frame. The filter type, for example, may be linear, bilinear, two-dimensional, bicubic, or may generally define any shape of filter support. Sometimes, the filter type may be presumed by the encoder and decoder, in which case the filter type is not included in the bitstream, but in other cases, filter type may be encoded along with filter coefficient information as described herein. The syntax data may also signal to the decoder how the filters were encoded (e.g., how the filter coefficients were encoded), as well as the ranges of the activity metric for which the different filters should be used.
In some instances, for each filter in a set of filters, the syntax data can include a zero flag indicating whether the filter has any non-zero coefficients. If the zero flag is set to a first value, then the decoder can reconstruct a filter of all zeros without receiving further information from the encoder. If the zero flag is set to a second value, then the decoder can receive additional syntax for reconstructing the filter. The zero flag may, for example, be a single bit where zero indicates a filter contains only zero filter coefficients and a one indicates the filter contains at least one non-zero filter coefficient.
In the case of a zero flag indicating that a filter contains at least one non-zero filter coefficient, additional syntax may, for example, describe other characteristics of the filters (e.g., filter types) that were used to filter the coded units of the slice or frame as well as include information enabling the decoder to reconstruct the coefficients of the filters. The filter type, for example, may be linear, bilinear, two-dimensional, bicubic, or may generally define any shape of filter support. Sometimes, the filter type may be presumed by the encoder and decoder, in which case the filter type is not included in the bitstream, but in other cases, filter type may be encoded along with filter coefficient information as described herein. The syntax data may also signal to the decoder how the filters were encoded (e.g., how the filter coefficients were encoded), as well as the ranges of the activity metric for which the different filters should be used.
Video encoder 122 may perform predictive coding in which a video block being coded is compared to a predictive frame (or other coded unit) in order to identify a predictive block. The differences between the current video block being coded and the predictive block are coded as a residual block, and prediction syntax is used to identify the predictive block. The residual block may be transformed and quantized. Transform techniques may comprise a DCT process or conceptually similar process, integer transforms, wavelet transforms, or other types of transforms. In a DCT process, as an example, the transform process converts a set of pixel values into transform coefficients, which may represent the energy of the pixel values in the frequency domain. Quantization is typically applied to the transform coefficients, and generally involves a process that limits the number of bits associated with any given transform coefficient.
Following transform and quantization, entropy coding may be performed on the quantized and transformed residual video blocks. Syntax elements, such as the filter information and prediction vectors defined during the encoding, may also be included in the entropy coded bitstream for each coded unit. In general, entropy coding comprises one or more processes that collectively compress a sequence of quantized transform coefficients and/or other syntax information. Scanning techniques, such as zig-zag scanning techniques, are performed on the quantized transform coefficients, e.g., as part of the entropy coding process, in order to define one or more serialized one-dimensional vectors of coefficients from two-dimensional video blocks. Other scanning techniques, including other scan orders or adaptive scans, may also be used, and possibly signaled in the encoded bitstream. In any case, the scanned coefficients are then entropy coded along with any syntax information, e.g., via content adaptive variable length coding (CAVLC), context adaptive binary arithmetic coding (CABAC), or another entropy coding process.
As part of the encoding process, encoded video blocks may be decoded in order to generate the video data used for subsequent prediction-based coding of subsequent video blocks. At this stage, filtering may be employed in order to improve video quality, and e.g., remove blockiness artifacts from decoded video. The filtered data may be used for prediction of other video blocks, in which case the filtering is referred to as “in-loop” filtering. Alternatively, prediction of other video blocks may be based on unfiltered data, in which case the filtering is referred to as “post filtering.”
On a frame-by-frame, slice-by-slice, or LCU-by-LCU basis, the encoder may select one or more sets of filters, and on a coded-unit-by-coded-unit basis may select one or more filters from the set(s). In some instances, filters may also be selected on a pixel-by-pixel basis or on a sub-CU basis, such as a 4×4 block basis. Both selection of the set of filters and selection of which filter from the set to apply can be made in a manner that promotes the video quality. Such sets of filters may be selected from pre-defined sets of filters, or may be adaptively defined to promote video quality. As an example, video encoder 122 may select or define several sets of filters for a given frame or slice such that different filters are used for different pixels of coded units of that frame or slice. In particular, for each input associated with a coded unit, several sets of filter coefficients may be defined, and the activity metric associated with the pixels of the coded unit may be used to determine which filter from the set of filters to use with such pixels. In some cases, video encoder 122 may apply several sets of filter coefficients and select one or more sets that produce the best quality video in terms of amount of distortion between a coded block and an original block, and/or the highest levels of compression. In any case, once selected, the set of filter coefficients applied by video encoder 122 for each coded unit may be encoded and communicated to video decoder 128 of destination device 118 so that video decoder 128 can apply the same filtering that was applied during the encoding process for each given coded unit.
As discussed in this disclosure, a zero flag can be used to reduce the number of bits needed to reconstruct filters that contain all zero coefficients. When an activity metric is used for determining which filter to use with a particular input for a coded unit, the selection of the filter for that particular coded unit does not necessarily need to be communicated to video decoder 128. Instead, video decoder 128 can also calculate the activity metric for the coded unit, and based on filter information previously provided by video encoder 122, match the activity metric to a particular filter.
FIG. 3 is a block diagram illustrating a video encoder 350 consistent with this disclosure. Video encoder 350 may correspond to video encoder 122 of device 120, or a video encoder of a different device. As shown in FIG. 3, video encoder 350 includes a prediction unit 332, adders 348 and 351, and a memory 334. Video encoder 350 also includes a transform unit 338 and a quantization unit 340, as well as an inverse quantization unit 342 and an inverse transform unit 344. Video encoder 350 also includes a de-blocking filter 347 and an adaptive filter unit 349. Video encoder 350 also includes an entropy encoding unit 346. Filter unit 349 of video encoder 350 may perform filtering operations and also may include a filter selection unit (FSU) 353 for identifying an optimal or preferred filter or set of filters to be used for decoding. Filter unit 349 may also generate filter information identifying the selected filters so that the selected filters can be efficiently communicated as filter information to another device to be used during a decoding operation.
During the encoding process, video encoder 350 receives a video block, such as an LCU, to be coded, and prediction unit 332 performs predictive coding techniques on the video block. Using the quadtree partitioning scheme discussed above, prediction unit 332 can partition the video block and perform predictive coding techniques on coding units of different sizes. For inter coding, prediction unit 332 compares the video block to be encoded, including sub-blocks of the video block, to various blocks in one or more video reference frames or slices in order to define a predictive block. For intra coding, prediction unit 332 generates a predictive block based on neighboring data within the same coded unit. Prediction unit 332 outputs the prediction block and adder 348 subtracts the prediction block from the video block being coded in order to generate a residual block.
For inter coding, prediction unit 332 may comprise motion estimation and motion compensation units that identify a motion vector that points to a prediction block and generates the prediction block based on the motion vector. Typically, motion estimation is considered the process of generating the motion vector, which estimates motion. For example, the motion vector may indicate the displacement of a predictive block within a predictive frame relative to the current block being coded within the current frame. Motion compensation is typically considered the process of fetching or generating the predictive block based on the motion vector determined by motion estimation. For intra coding, prediction unit 332 generates a predictive block based on neighboring data within the same coded unit. One or more intra-prediction modes may define how an intra prediction block can be defined.
After prediction unit 332 outputs the prediction block and adder 48 subtracts the prediction block from the video block being coded in order to generate a residual block, transform unit 38 applies a transform to the residual block. The transform may comprise a discrete cosine transform (DCT) or a conceptually similar transform such as that defined by a coding standard such as the HEVC standard. Wavelet transforms, integer transforms, sub-band transforms or other types of transforms could also be used. In any case, transform unit 338 applies the transform to the residual block, producing a block of residual transform coefficients. The transform may convert the residual information from a pixel domain to a frequency domain.
Quantization unit 340 then quantizes the residual transform coefficients to further reduce bit rate. Quantization unit 340, for example, may limit the number of bits used to code each of the coefficients. After quantization, entropy encoding unit 346 scans the quantized coefficient block from a two-dimensional representation to one or more serialized one-dimensional vectors. The scan order may be pre-programmed to occur in a defined order (such as zig-zag scanning, horizontal scanning, vertical scanning, combinations, or another pre-defined order), or possibly adaptive defined based on previous coding statistics.
Following this scanning process, entropy encoding unit 346 encodes the quantized transform coefficients (along with any syntax elements) according to an entropy coding methodology, such as CAVLC or CABAC, to further compress the data. Syntax elements included in the entropy coded bitstream may include prediction syntax from prediction unit 332, such as motion vectors for inter coding or prediction modes for intra coding. Syntax elements included in the entropy coded bitstream may also include filter information from filter unit 349, which can be encoded in the manner described herein.
CAVLC is one type of entropy coding technique supported by the ITU H.264/MPEG4, AVC standard, which may be applied on a vectorized basis by entropy encoding unit 346. CAVLC uses variable length coding (VLC) tables in a manner that effectively compresses serialized “runs” of transform coefficients and/or syntax elements. CABAC is another type of entropy coding technique supported by the ITU H.264/MPEG4, AVC standard, which may be applied on a vectorized basis by entropy encoding unit 346. CABAC involves several stages, including binarization, context model selection, and binary arithmetic coding. In this case, entropy encoding unit 346 codes transform coefficients and syntax elements according to CABAC. Like the ITU H.264/MPEG4, AVC standard, the emerging HEVC standard may also support both CAVLC and CABAC entropy coding. Furthermore, many other types of entropy coding techniques also exist, and new entropy coding techniques will likely emerge in the future. This disclosure is not limited to any specific entropy coding technique.
Following the entropy coding by entropy encoding unit 346, the encoded video may be transmitted to another device or archived for later transmission or retrieval. Again, the encoded video may comprise the entropy coded vectors and various syntax, which can be used by the decoder to properly configure the decoding process. Inverse quantization unit 342 and inverse transform unit 344 apply inverse quantization and inverse transform, respectively, to reconstruct the residual block in the pixel domain. Summer 351 adds the reconstructed residual block to the prediction block produced by prediction unit 332 to produce a pre-deblocked reconstructed video block, sometimes referred to as pre-deblocked reconstructed image. De-blocking filter 347 may apply filtering to the pre-deblocked reconstructed video block to improve video quality by removing blockiness or other artifacts. The output of the de-blocking filter 347 can be referred to as a post-deblocked video block, reconstructed video block, or reconstructed image.
Filter unit 349 can be configured to receive multiple inputs. In the example of FIG. 3, filter unit 349 receives as input the post-deblocked reconstructed image (RI), pre-deblocked reconstructed image (pRI), the prediction image (PI), and the reconstructed residual block (EI). Filter unit 349 can use any of these inputs either individually or in combination to produce a reconstructed image to store in memory 334. Additionally, as will be discussed in more detail below, based on an activity metric, one or more filters can be selected to be applied to the input(s). In one example, the output of filter unit 349 may be one additional filter applied to RI. In another example, the output of filter unit 349 may be one additional filter applied to pRI. In other examples, however, the output of filter unit 349 may be based on multiple inputs. For example, filter unit 349 may apply a first filter to pRI and then use the filtered version of pRI in conjunction with filtered versions of EI and PI to create a reconstructed image. In instances where the output of filter unit 349 is the product of one additional filter being applied to a single input, filter unit 349 may in fact apply filters to the other inputs, but those filters might have all zero coefficients. Similarly, if the output of filter unit 349 is the product of applying three filters to three inputs, filter unit 349 may in fact apply a filter to the fourth input, but that filter might have all zero coefficients. As will be discussed in more detail below, techniques in which filter unit 349 applies the same sequence of filters to multiple inputs for all coded units that are to be filtered can reduce the complexity of implementing filter unit 349 in a device. The application of filters that have all zero coefficients can increase the number of possible ways in which filter unit 349 can process multiple inputs, and thus, can potentially improve coding quality.
Filtering by filter unit 349 may improve compression by generating predictive video blocks that more closely match video blocks being coded than unfiltered predictive video blocks. After filtering, the reconstructed video block may be used by prediction unit 332 as a reference block to inter-code a block in a subsequent video frame or other coded unit. Although filter unit 349 is shown “in-loop,” the techniques of this disclosure could also be used with post filters, in which case non-filtered data (rather than filtered data) would be used for purposes of predicting data in subsequent coded units.
For a slice or frame, filter unit 349 may select sets of filters for each input in a manner that promotes the video quality. For example, filter unit 349 may select sets of filters from pre-defined sets of coefficients, or may adaptively define filters in order to promote video quality or improved compression. One or more of the filters for each set may be filters that have all zero coefficients. Filter unit 349 may select or define one or more sets of filters for a given coded unit such that the same set(s) of filters are used for pixels of different video blocks of that coded unit. For a particular frame, slice, or LCU, filter unit 349 may apply several sets of filters to multiple inputs, and FSU 353 may select the set that produces the best quality video or the highest levels of compression. Alternatively, FSU 353 may train a new filter by analyzing the auto-correlations and cross-correlations between multiple inputs and an original image. A new set of filters may, for example, be determined by solving Wienter-Hopt equations based on the auto- and cross-correlations. Regardless of whether a new set of filters is trained or an existing set of filters are selected, filter unit 349 generates syntax for inclusion in the bit stream that enables a decoder to also identify the set or sets of filters to be used for the particular frame or slice.
According to this disclosure, for each pixel of a coded unit within the frame or slice, filter unit 349 may select which filter from the set of filters is to be used based on an activity metric that quantifies activity associated with one or more sets of pixels within the coded unit. In this way, FSU 353 may determine sets of filters for a higher level coded unit such as a frame or slice, while filter unit 349 determines which filter(s) from the set(s) is to be used for a particular pixel of a lower level coded unit based on the activity associated with the pixels of that lower level coded unit. Activity may be indicated in terms of pixel value variance within a coded unit. More variance in the pixel values in the coded unit may indicate higher levels of pixel activity, while less variance in the pixel values may indicate lower levels of pixel activity. Different filters (i.e. different filter coefficients) may result in better filtering (e.g., higher image quality) depending on the level of pixel variance, i.e., activity. The pixel variance may be quantified by an activity metric, which may comprise a sum-modified Laplacian value as discussed in greater detail below. However, other types of activity metrics may also be used.
Instead of a single filter for each input, a set of M filters may be used for each input. Depending on design preferences, M may for example be as few as 2 or as great as 16, or even higher. A large number of filters per input may improve video quality, but also may increase overhead associated with signaling sets of filters from encoder to decoder. The set of M filters can be determined by FSU 353 as described above and transmitted to the decoder for each frame or slice. A segmentation map can be used to indicate how a coded unit is segmented and whether or not a particular sub-unit of the coded unit is to be filtered. The segmentation map, may for example, include for a coded unit an array of split flags as described above as well an additional bit signaling whether each sub-coded unit is to be filtered. For each input associated with a pixel of a coded unit that is to be filtered, a specific filter from the set of filters can be chosen based on the activity metric. The activity metric can be calculated using a sum-modified Laplacian for pixel (i,l) as follows:




  
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As one example, a 7×7 (K, L=3) group of surrounding pixels may be used for calculation of the sum-modified Laplacian value. The particular filter from the set of M filters to be used for a particular range of sum-modified Laplacian values can also be sent to the decoder with the set of M filters. Filter coefficients can be coded using prediction from coefficients transmitted for previous frames or other techniques. Filters of various shapes and sizes, including for example 1×1, 3×3, 5×5, 7×7, and 9×9 filters with diamond shape support or square shape support might be used.

The indexing of sum-modified Laplacian values for inputs to filters can be implemented in multiple ways. For example, in some implementations each input might have a unique set of filters, while in some implementations inputs share a common set of filters. Additionally, in some implementations, a sum-modified Laplacian value for each input might be used to identify a particular filter for each input. In other implementations, however, a sum-modified Laplacian value for a single input might be used to identify filters for all the inputs. In yet other implementations, a sum-modified Laplacian value for a first input might be used to identify a filter for a second, different input.
In accordance with this disclosure, filter unit 349 performs coding techniques with respect to filter information that may reduce the amount of data needed to encode and convey filter information from encoder 350 to another device. Again, for each frame or slice, filter unit 349 may define or select one or more sets of filter coefficients to be applied to the pixels of coded units for that frame or slice. Filter unit 349 applies the filter coefficients in order to filter video blocks of reconstructed video frames stored in memory 334, which may be used for predictive coding consistent with in-loop filtering. Filter unit 349 can encode the filter coefficients as filter information, which is forwarded to entropy encoding unit 346 for inclusion in the encoded bitstream.
The filter information can include a zero flag for each filter to reduce the number of coded bits needed to transfer the filter coefficients from video encoder 350 to a decoder. The zero flag can be a one-bit syntax element in a header of a frame, slice, largest coded unit, coded unit, or other series of video blocks. If all the coefficients for a particular filter are zero, then video encoder 350 can transmit to the decoder a zero flag set to a first value. Upon receiving a zero flag set to the first value, the decoder can reconstruct the filter without actually receiving data identifying all the zero coefficients from the encoder. If the coefficients for a particular filter include at least one non-zero coefficient, then video encoder 350 can transmit to the decoder a zero flag set to a second value. Upon receiving a zero flag set to the second value, the decoder reconstructs the filter based on coefficients subsequently received from the encoder. Thus, in order to reconstruct all the coefficients for filters of a set of filters, video encoder 350 may only need to transmit filter coefficients to a decoder for those cases where at least one filter coefficient is non-zero.
Additionally, for filters that do contain non-zero coefficients, the techniques of this disclosure may also exploit the fact that some of the filter coefficients defined or selected by FSU 353 may be very similar to other filter coefficients applied with respect to the pixels of coded units of another frame or slice. The same type of filter may be applied for different frames or slices (e.g., the same filter support), but the filters may be different in terms of filter coefficient values associated with the different indices of the filter support. Accordingly, in order to reduce the amount of data needed to convey such filter coefficients, filter unit 349 may predictively encode one or more filter coefficients to be used for filtering based on the filter coefficients of another coded unit, exploiting any similarities between the filter coefficients. In some cases, however, it may be more desirable to encode the filter coefficients directly, e.g., without using any prediction. Various techniques, such as techniques that exploit the use of an activity metric to define when to encode the filter coefficients using predictive coding techniques and when to encode the filter coefficients directly without any predictive coding, can be used for efficiently communicating filter coefficients to a decoder. Additionally, symmetry may also be imposed so that a subset of coefficients (e.g., 5, −2, 10) known by the decoder can be used to define the full set of coefficients (e.g., 5, −2, 10, 10, −2, 5). Symmetry may be imposed in both the direct and the predictive coding scenarios.
FIG. 4 is a block diagram illustrating an example of a video decoder 460, which decodes a video sequence that is encoded in the manner described herein. The received video sequence may comprise an encoded set of image fames, a set of frame slices, a commonly coded group of pictures (GOPs), or a wide variety of types of series of video blocks that include encoded video blocks and syntax to define how to decode such video blocks.
Video decoder 460 includes an entropy decoding unit 452, which performs the reciprocal decoding function of the encoding performed by entropy encoding unit 346 of FIG. 3. In particular, entropy decoding unit 452 may perform CAVLC or CABAC decoding, or any other type of entropy decoding used by video encoder 350. Entropy decoded video blocks in a one-dimensional serialized format may be inverse scanned to convert one or more one-dimensional vectors of coefficients back into a two-dimensional block format. The number and size of the vectors, as well as the scan order defined for the video blocks may define how the two-dimensional block is reconstructed. Entropy decoded prediction syntax may be sent from entropy decoding unit 452 to prediction unit 454, and entropy decoded filter information may be sent from entropy decoding unit 452 to filter unit 459.
Video decoder 460 also includes a prediction unit 454, an inverse quantization unit 456, an inverse transform unit 458, a memory and a summer 464. In addition, video decoder 460 also includes a de-blocking filter 457 that filters the output of summer 464. Consistent with this disclosure, filter unit 459 may receive entropy decoded filter information that includes one or more filters to be applied to one or more inputs. Although not shown on FIG. 4, de-blocking filter 457 may also receive entropy decoded filter information that includes one or more filters to be applied.
The filters applied by filter unit 459 may be defined by sets of filter coefficients. Filter unit 459 may be configured to generate the sets of filter coefficients based on the filter information received from entropy decoding unit 452. For each filter in a set of filters, the filter information may include a zero flag, which can be a one-bit syntax element in a header of a series of video blocks, e.g., an LCU header, a frame header, a slice header, a GOP header, a sequence header, or the like. In other examples, the syntax elements that define the filter information could also be included in a footer or other data structure. If filter unit 459 receives a zero flag set to a first value indicating the filter does not contain non-zero coefficients, then filter unit 459 can reconstruct the filter without actually receiving data identifying all the zero coefficients from the encoder. If filter unit 459 receives a zero flag of a second value indicating the coefficients for a particular filter include at least one non-zero coefficient, filter unit 459 can reconstruct the filter based on subsequent filter information. Thus, in order to reconstruct a filter, an encoder may only need to transmit filter coefficients to video decoder 460 for those cases where at least one filter coefficient is non-zero.
The filter information may include additional signaling syntax that signals to the decoder the manner of encoding used for any given set of coefficients. In some implementations, the filter information may for example, also include activity metric ranges for which any given set of coefficients should be used. Following decoding of the filters, filter unit 459 can filter the pixel values of decoded video blocks based on the one or more sets of filter coefficients and the signaling syntax that includes activity metric ranges for which the different sets of filter coefficients should be used. The activity metric ranges may be defined by a set of activity values that define the ranges of activity metrics used to define the type of encoding used (e.g., predictive or direct).
Filter unit 459 may receive in the bit stream a set of filters for each frame or slice. For each coded unit within the frame or slice, filter unit 459 can calculate one or more activity metrics associated with the decoded pixels of a coded unit for multiple inputs (i.e. PI, EI, pRI, and RI) in order to determine which filter(s) of the set(s) to apply to each input. For a first range of the activity metric, filter unit 459 may apply a first filter, for a second range of the activity metric filter unit 459 may apply a second filter, and so on. In some implementations four ranges may map to four different filters, although any number of ranges and filters may be used. The filter may generally assume any type of filter support shape or arrangement. The filter support refers to the shape of the filter with respect to a given pixel being filtered, and the filter coefficients may define weighting applied to neighboring pixel values according to the filter support. Sometimes, the filter type may be presumed by the encoder and decoder, in which case the filter type is not included in the bitstream, but in other cases, filter type may be encoded along with filter coefficient information as described herein. The syntax data may also signal to the decoder how the filters were encoded (e.g., how the filter coefficients were encoded), as well as the ranges of the activity metric for which the different filters should be used.
Prediction unit 454 receives prediction syntax (such as motion vectors) from entropy decoding unit 452. Using the prediction syntax, prediction unit 454 generates the prediction blocks that were used to code video blocks. Inverse quantization unit 456 performs inverse quantization, and inverse transform unit 458 performs inverse transforms to change the coefficients of the residual video blocks back to the pixel domain. Adder 464 combines each prediction block with the corresponding residual block output by inverse transform unit 458 in order to reconstruct the video block.
Filter unit 459 generates the filter coefficients to be applied for each input of a coded unit, and then applies such filter coefficients in order to filter the reconstructed video blocks of that coded unit. The filtering, for example, may comprise additional deblock filtering that smoothes edges and/or eliminates artifacts associated with video blocks, denoise filtering to reduce quantization noise, or any other type of filtering that can improve coding quality. The filtered video blocks are accumulated in memory 462 in order to reconstruct decoded frames (or other decodable units) of video information. The decoded units may be output from video decoder 460 for presentation to a user, but may also be stored for use in subsequent predictive decoding.
In the field of video coding, it is common to apply filtering at the encoder and decoder in order to enhance the quality of a decoded video signal. Filtering can be applied via a post-filter, in which case the filtered frame is not used for prediction of future frames. Alternatively, filtering can be applied “in-loop,” in which case the filtered frame may be used to predict future frames. A desirable filter can be designed by minimizing the error between the original signal and the decoded filtered signal. Typically, such filtering has been based on applying one or more filters to a reconstructed image. For example, a deblocking filter might be applied to a reconstructed image prior to the image being stored in memory, or a deblocking filter and one additional filter might be applied to a reconstructed image prior to the image being stored in memory. Techniques of the present disclosure include the application of filters to inputs other than just a reconstructed image. Additionally, as will be discussed more below, filters for those multiple inputs can be selected based on Laplacian filter indexing.
In a manner similar to the quantization of transform coefficients, the coefficients of the filter h(k,l), where k=−K, . . . , K, and l=−L, . . . , L may also be quantized. K and L may represent integer values. The coefficients of filter h(k,l) may be quantized as:

f(k,l)=round(normFact·h(k,l))

where normFact is a normalization factor and round is the rounding operation performed to achieve quantization to a desired bit-depth. Quantization of filter coefficients may be performed by filter unit 349 of FIG. 3 during the encoding, and de-quantization or inverse quantization may be performed on decoded filter coefficients by filter unit 459 of FIG. 4. Filter h(k,l) is intended to generically represent any filter. For example, filter h(k,l) could be applied to any one of multiple inputs. In some instances multiple inputs associated with a video block will utilize different filters, in which case multiple filters similar to h(k,l) may be quantized and de-quanitzed as described above.

The quantized filter coefficients are encoded and sent from source device associated with encoder 350 to a destination device associated with decoder 460 as part of an encoded bitstream. In the example above, the value of normFact is usually equal to 2n although other values could be used. Larger values of normFact lead to more precise quantization such that the quantized filter coefficients f (k, l) provide better performance. However, larger values of normFact may produce coefficients f (k, l) that require more bits to transmit to the decoder.
At decoder 460 the decoded filter coefficients f (k,l) may be applied to the appropriate input. For example, if the decoded filter coefficients are to be applied to RI, the filter coefficients may be applied to the post-deblocked reconstructed image RI(i,j), where i=0, . . . , M and j=0, . . . , N as follows:




  
    
      R
      ~
    
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      ⁡
      
        (
        
          i
          ,
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        )
      
    
  
  =
  
    
      ∑
      
        k
        =
        
          -
          K
        
      
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        ∑
        
          l
          =
          
            -
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          f
          ⁡
          
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              k
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            ⁡
            
              (
              
                
                  i
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              ∑
              
                k
                =
                
                  -
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                  =
                  
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The variables M, N, K and L may represent integers. K and L may define a block of pixels that spans two-dimensions from −K to K and from −L to L. Filters applied to other inputs can be applied in an analogous manner.

The techniques of this disclosure may improve the performance of a post-filter or in-loop filter, and may also reduce number of bits needed to transmit filter coefficients f(k, l). In some cases, a number of different post-filters or in-loop filters are transmitted to the decoder for each series of video block, e.g., for each frame, slice, portion of a frame, group of frames (GOP), or the like. For each filter, additional information is included in the bitstream to identify the coded units, macroblocks and/or pixels for which a given filter should be applied.
The frames may be identified by frame number and/or frame type (e.g., I-frames, P-frames or B-frames). I-frames refer to intra-frames that are intra-predicted. P-frames refer to predictive frames that have video blocks predicted based on one list of data (e.g., one previous frame). B-frames refer to bidirectional predictive frames that are predicted based on two lists of data (e.g., a previous and subsequent frame). Macroblocks can be identified by listing macroblock types and/or range of quantization parameter (QP) values use to reconstruct the macroblock.
The filter information may also indicate that only pixels for which the value of a given measure of local characteristic of an image, called an activity metric, is within specified range should be filtered with a particular filter. For example, for pixel (i,j) the activity metric may comprise a sum-modified Laplacian value calculated as follows:




  
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wherein k represents a value of a summation of pixel values from −K to K and l represents a value of a summation from −L to L for a two-dimensional window that spans from −K to K and −L to L, wherein i and j represent pixel coordinates of the pixel data, RI(i,j) represents a given pixel value at coordinates i and j, and var(i,j) is the activity metric. An activity metric may similarly be found for pRI(i,j), PI(i,j), and EI(i,j).

Filter coefficients f(k, l), for any input, may be coded using prediction from coefficients transmitted for previous coded units. For each input of a coded unit m (e.g., each frame, slice or GOP), the encoder may encode and transmit a set of M filters:
gim, wherein i=0, . . . ,M−1.
For each filter, the bitstream may be encoded to identify a range of values of activity metric value var for which the filter should be used.
For example, filter unit 349 of encoder 350 may indicate that filter:
gom 
should be used for pixels for which activity metric value var is within interval [0, var0), i.e., var≧0 and var<var0. Furthermore, filter unit 349 of encoder 350 may indicate that filter:
gim where i=1, . . . , M−2,
should be used for pixels for which activity metric value var is within interval [vari−1,vari). In addition, filter unit 349 of encoder 350 may indicate that filter:
gM−1m 
should be used for pixels for which the activity metric var when var>varM−2. As described above, filter unit 349 may use one set of filters for all inputs, or alternatively, may use a unique set of filters for each input.
The filter coefficients can be predicted using reconstructed filter coefficients used in a previous coded unit. The previous filter coefficients may be represented as:
ftn where i=0, . . . ,N−1,
In this case, the number of the coded unit n may be used to identify one or more filters used for prediction of the current filters, and the number n may be sent to the decoder as part of the encoded bitstream. In addition, information can be encoded and transmitted to the decoder to identify values of the activity metric var for which predictive coding is used.
For example, assume that for a currently coded frame m, coefficients:
grm 
are transmitted for the activity metric values [varr−1, varr). The filter coefficients of the frame m are predicted from filter coefficients of the frame n. Assume that filter
fsn 
is used in frame n for pixels for which the activity metric is within an interval [vars−1, vars) where vars−1==varr−1 and vars>varr. In this case, interval [varr−1, varr) is contained within interval [vars−1, vars). In addition, information may be transmitted to the decoder indicating that prediction of filter coefficients should be used for activity values [vart−1, vart) but not for activity values [vart, vart+1) where vart−1==varr−1 and vart+1==varr.
The relationship between intervals [varr−1−1, varr), [vars−1, vars), [vart−1, vart) and [vart, vart+1) is depicted in FIG. 5. In this case, the final values of the filter coefficients:
ftm 
used to filter pixels with activity metric in the interval [vart−1, vart) are equal to the sum of coefficients:
fsn and grm 
Accordingly:

ftm(k,l)=fsn(k,l)+grm(k,l),k=−K, . . . , K, l=−L, . . . , L. 

In addition, filter coefficients:

ft+1m 
that are used for pixels with activity metric [vart, vart+1) are equal to filter coefficients:
glm.
Therefore:

ft+1m(k,l)=grm(k,l),k=−K, . . . , K, l=−L, . . . , L. 

The amplitude of the filter coefficients g(k, l) depends on k and l values. Usually, the coefficient with the biggest amplitude is the coefficient g(0,0). The other coefficients which are expected to have large amplitudes are the coefficients for which value of k or l is equal to 0. This phenomenon may be utilized to further reduce amount of bits needed to transmit the coefficients. The index values k and l may define locations within a known filter support.
The coefficients:
gim(k,l), i=0, . . . ,M−1
for each frame m may be coded using parameterized variable length codes such as Golomb or exp-Golomb codes defined according to a parameter p. By changing the value of parameter p that defines the parameterized variable length codes, these codes can be used to efficiently represent wide range of source distributions. The distribution of coefficients g(k,l) (i.e., their likelihood to have large or small values) depends on values of k and l. Hence, to increase coding efficiency, for each frame m, the value of parameter p is transmitted for each pair (k,l). The parameter p can be used for parameterized variable length coding when encoding coefficients:
gim(k,l) where k=−K, . . . , K, l=−L, . . . , L.
FIG. 6 shows an example of a filter unit 600 configured to implement techniques of this disclosure. The functionality of filter unit 600 may, for example, be incorporated into filter unit 349 of FIG. 3 or filter unit 459 of FIG. 4. Filter unit 600 includes a plurality of filter modules 610A-C (collectively “filter modules 610”). Each filter module can be configured to receive one or more inputs. In this particular example, filter module 610A receives the input pRI and applies a filter to generate a filtered version of pRI, shown on FIG. 6 as pRI′. Filter module 610B receives as input pRI's, PI, and EI. Using these three inputs, Filter Module 2 610B can generate an output, shown at FIG. 6 as R′, by applying the following three filters as follows:




  
    R
    ′
  
  =
  
    
      
        ∑
        
          i
          =
          1
        
        M
      
      ⁢
      
        
          w
          i
        
        ·
        
          pRI
          i
        
      
    
    +
    
      
        ∑
        
          i
          =
          1
        
        N
      
      ⁢
      
        
          w
          
            M
            +
            i
          
        
        ·
        
          PI
          i
        
      
    
    +
    
      
        ∑
        
          i
          =
          1
        
        O
      
      ⁢
      
        
          w
          
            M
            +
            N
            +
            i
          
        
        ·
        
          EI
          i
        
      
    
  




Filter module 610C can generate an output (R′′) by applying the two filters as follows:





  
    R
    ′′
  
  =
  
    
      
        ∑
        
          i
          =
          1
        
        M
      
      ⁢
      
        
          w
          i
        
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          R
          i
          ′
        
      
    
    +
    
      
        ∑
        
          i
          =
          1
        
        N
      
      ⁢
      
        
          w
          
            M
            +
            i
          
        
        ·
        
          RI
          i
        
      
    
  




By applying filters of all zeros, different outputs can be achieved. For example, if filter module 610A applies a filter of all zeros to pRI, and filter module 610B applies filters of all zeros to PI and EI, then the output of filter module 610B will similarly be zero, meaning the output of filter module 610C will simply be a filtered version of RI. In another implementation, all of the filters applied to the various inputs can be chosen from a set of filters based on an activity metric, such as via Laplacian filter indexing. As mentioned previously, the indexing of sum-modified Laplacian values for inputs to filters can be implemented in multiple ways. For example, in some implementations each input might have a unique set of filters, while in some implementations inputs share a common set of filters. Additionally, in some implementations, a sum-modified Laplacian value for each input might be used to identify a particular filter for each input. In other implementations, however, a sum-modified Laplacian value for a single input might be used to identify filters for all the inputs. In yet other implementations, a sum-modified Laplacian value for a first input might be used to identify a filter for a second, different input.
FIG. 7 is a flow diagram illustrating an encoding technique consistent with this disclosure. As shown in FIG. 3, video encoder 350 encodes pixel data of a series of video blocks. The series of video blocks may comprise a frame, a slice, a group of pictures (GOP), or another independently decodable unit. The pixel data may be arranged in coded units, and video encoder 350 may encode the pixel data by encoding the coded units in accordance with a video encoding standard such as the HEVC standard. For a frame or slice, FSU 353 can identify a set of filters to be used for the frame or slice (710). FSU 353 may identify one set of filters for all inputs or may identify a set of filters for each input.
As part of the video encoding process, prediction unit 332 performs prediction based coding and determines a quadtree based partitioning scheme for a particular coded unit (720). Further, as part of the video encoding process, filter unit 349 of video encoder 350 selects, based on Laplacian filter indexing, one or more filters from the set of filters to be used for sub-coded units of the particular coded unit of the frame, slice, or LCU (730). The one or more filters may be applied to one or more inputs, as described above. This filtering may be used to improve video coding by generally making a decoded image more similar to an original image. Filter unit 349 is shown as being in-loop, which means that the filtered data is used for predictive encoding of later video blocks. However, filter unit 349 could alternatively apply post filtering, in which case the unfiltered data would be used for predictive encoding of later video blocks.
Video encoder 350 outputs an encoded bitstream for the coded unit (740), which includes encoded pixel data and the encoded filter data. The encoded filter data may include signaling information for identifying the set of filters to be used and may also include signaling information that identifies how the filters were encoded and the ranges of the activity metric for which the different filters should be applied. The encoded pixel data may include among other types of data, a segmentation map for a particular coded unit.
FIG. 8 is a flow diagram illustrating a decoding technique consistent with this disclosure. As shown in FIG. 8, video decoder 460 receives an encoded bitstream including encoded video data and encoded filter data (810). Video decoder 460 decodes the filter data to reconstruct one or more sets of filters as well as ranges for an activity metric for determining when to apply a particular filter from the set of filters (820). As discussed above, the filter data may include a set of filters to be used with all inputs or may include a set of filters for each input. As described above in relation to FIG. 4, the reconstruction process can produce a plurality of inputs (i.e. RI, pRI, PI, and EI) for filter unit 459. Video decoder 460 decodes the video data to generate blocks of pixel data (830). The pixel data may include, among other types of data, a segmentation map. In particular, video decoder 460 may generate pixel data by performing block-based video reconstruction consistent with a video standard such as the newly emerging HEVC standard or a similar block-based video coding standard.
Based on a segmentation map for a coded unit, video decoder 460 can determine if a sub-coded unit of the coded unit is to be filtered by filter unit 459. If a sub-unit is to be filtered, then filter unit 459 can determine one or more sum-modified Laplacian values for the sub-coded unit, and based on Laplacian filter indexing, identify one or more filters to be used with one or more inputs of the sub-coded unit (840).
FIG. 9 is a flow diagram illustrating an encoding technique consistent with this disclosure. As shown in FIG. 3, video encoder 350 encodes pixel data of a series of video blocks. The series of video blocks may comprise a frame, a slice, a group of pictures (GOP), an entire sequence of video data, or another decodable set of video data. The pixel data may be arranged in coded units, and video encoder 350 may encode the pixel data by encoding the coded units in accordance with a video encoding standard such as the HEVC standard. For a frame or slice, FSU 353 can identify a set of filters to be used for the frame or slice (910). FSU 353 may identify one set of filters for all inputs or may identify a set of filters for each input. In some instance, one or more of the filters may include all zero coefficients.
As part of the video encoding process, prediction unit 332 performs prediction based coding and determines a quadtree based partitioning scheme for a particular coded unit (920). Further, as part of the video encoding process, filter unit 349 of video encoder 350 selects, based on Laplacian filter indexing, one or more filters from the set of filters to be used for sub-coded units of the particular coded unit of the frame, slice, or LCU (930). The one or more filters may be applied to one or more inputs, as described above. This filtering may be used to improve video coding by generally making a decoded image more similar to an original image. Filter unit 349 is shown as being in-loop, which means that the filtered data is used for predictive encoding of later video blocks. However, filter unit 349 could alternatively apply post filtering, in which case the unfiltered data would be used for predictive encoding of later video blocks.
Video encoder 350 outputs an encoded bitstream for the coded unit, which includes encoded pixel data and the encoded filter data with one or more zero flags (940). The encoded filter data may include signaling information, including a zero flag for each filter, for identifying the set of filters to be used and may also include signaling information that identifies how the filters were encoded and the ranges of the activity metric for which the different filters should be applied. The encoded pixel data may include among other types of data, a segmentation map for a particular coded unit.
FIG. 10 is a flow diagram illustrating a decoding technique consistent with this disclosure. As shown in FIG. 8, video decoder 460 receives an encoded bitstream including encoded video data and encoded filter data with one or more zero flags (1010). Video decoder 460 decodes the filter data to reconstruct one or more sets of filters as well as ranges for an activity metric for determining when to apply a particular filter from the set of filters (1020). As discussed above, the filter data may include a set of filters to be used with all inputs or may include a set of filters for each input. As described above in relation to FIG. 4, the reconstruction process can produce a plurality of inputs (i.e. RI, pRI, PI, and EI) for filter unit 459. Video decoder 460 decodes the video data to generate blocks of pixel data (1030). The pixel data may include, among other types of data, a segmentation map. In particular, video decoder 460 may generate pixel data by performing block-based video reconstruction consistent with a video standard such as the newly emerging HEVC standard or a similar block-based video coding standard.
Based on a segmentation map for a coded unit, video decoder 460 can determine if a sub-coded unit of the coded unit is to be filtered by filter unit 459. If a sub-unit is to be filtered, then filter unit 459 can determine one or more sum-modified Laplacian values for the sub-coded unit, and based on Laplacian filter indexing, identify one or more filters to be used with one or more inputs of the sub-coded unit (1040).
The foregoing disclosure has been simplified to some extent in order to convey details. For example, the disclosure generally describes sets of filters being transmitted on a per-frame or per-slice basis, but sets of filters may also be transmitted on a per-sequence basis, per-group of picture basis, per-group of slices basis, per-CU basis, per-LCU basis, or other such basis. In general, filters may be transmitted for any grouping of one or more coded units. Additionally, in implementation, there may be numerous filters per input per coded unit, numerous coefficients per filter, and numerous different levels of variance with each of the filters being defined for a different range of variance. For example, in some cases there may be sixteen or more filters defined for each input of a coded unit and sixteen different ranges of variance corresponding to each filter.
Each of the filters for each input may include many coefficients. In one example, the filters comprise two-dimensional filters with 81 different coefficients defined for a filter support that extends in two-dimensions. However, the number of filter coefficients that are transmitted for each filter may be fewer than 81 in some cases. Coefficient symmetry, for example, may be imposed such that filter coefficients in one dimension or quadrant may correspond to inverted or symmetric values relative to coefficients in other dimensions or quadrants. Coefficient symmetry may allow for 81 different coefficients to be represented by fewer coefficients, in which case the encoder and decoder may assume that inverted or mirrored values of coefficients define other coefficients. For example, the coefficients (5, −2, 10, 10, −2, 5) may be encoded and transmitted as the subset of coefficients (5, −2, 10). In this case, the decoder may know that these three coefficients define the larger symmetric set of coefficients (5, −2, 10, 10, −2, 5).
The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, and integrated circuit (IC) or a set of ICs (i.e., a chip set). Any components, modules or units have been described provided to emphasize functional aspects and does not necessarily require realization by different hardware units.
Accordingly, the techniques described herein may be implemented in hardware, software, firmware, or any combination thereof. If implemented in hardware, any features described as modules, units or components may be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be realized at least in part by a computer-readable medium comprising instructions that, when executed in a processor, performs one or more of the methods described above. The computer-readable medium may comprise a computer-readable storage medium and may form part of a computer program product, which may include packaging materials. The computer-readable storage medium may comprise random access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), FLASH memory, magnetic or optical data storage media, and the like. The techniques additionally, or alternatively, may be realized at least in part by a computer-readable communication medium that carries or communicates code in the form of instructions or data structures and that can be accessed, read, and/or executed by a computer.
The code may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, an application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structure or any other structure suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein may be provided within dedicated software modules or hardware modules configured for encoding and decoding, or incorporated in a combined video codec. Also, the techniques could be fully implemented in one or more circuits or logic elements.
Various aspects of the disclosure have been described. These and other aspects are within the scope of the following claims.

## Claims

1. A method of decoding video data, the method comprising:
receiving a syntax element, a first value for the syntax element indicating that coefficients of a filter comprise at least one non-zero coefficient and a second value for the syntax element indicating the coefficients of the filter comprise all zero coefficients;
based on the value of the syntax element being set to the second value, reconstructing the filter with all zero coefficients;
applying a first filter from a first set of filters to a first input based on a first activity metric to generate a first filtered result, the first input comprising a post-deblocked reconstructed image, the set of filters including the filter with all zero coefficients;
and
generating a filtered image based on the first filtered result.

2. The method of claim 1, wherein the first activity metric comprises a sum-modified Laplacian value.

3. The method of claim 2, wherein the sum-modified Laplacian value comprises var(i,j) defined approximately according to the following equation:




  
    var
    ⁡
    
      (
      
        i
        ,
        j
      
      )
    
  
  =
  
    
      
        ∑
        
          k
          =
          
            -
            K
          
        
        K
      
      ⁢
      
        ∑
        
          l
          =
          
            -
            L
          
        
        L
      
    
    |
    
      
        2
        ⁢
        
          R
          ⁡
          
            (
            
              
                i
                +
                k
              
              ,
              
                j
                +
                l
              
            
            )
          
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              -
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              +
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
    
    |
    
      +
      
        |
        
          
            2
            ⁢
            
              R
              ⁡
              
                (
                
                  
                    i
                    +
                    k
                  
                  ,
                  
                    j
                    +
                    l
                  
                
                )
              
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  -
                  1
                
              
              )
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  +
                  1
                
              
              )
            
          
        
        |
      
    
  




wherein k represents a value of a summation from −K to K and 1 represents a value of a summation from −L to L for a two-dimensional window that spans from −K to K and −L to L, wherein i and j represent pixel coordinates of the pixel data, R(i,j) represents a given pixel value at coordinates i and j, and var(i,j) is the first activity metric.

4. The method of claim 1, wherein the first activity metric is an activity metric of the post-deblocked reconstructed image.

5. The method of claim 1, wherein a first range of values for the first activity metric is indexed to the first filter and a different range of values for the first activity metric is indexed to a different filter of the first set of filters.

6. The method of claim 1, the method further comprising:
in response to the value of the syntax element being set to the first value, reconstructing the coefficients of the filter based on additional information received from a video encoder, the received additional information identifying the coefficients of the filter.

7. The method of claim 1, wherein the syntax element is a single bit.

8. The method of claim 1, wherein the syntax element is part of a header of a series of video blocks.

9. The method of claim 1, further comprising:
applying a second filter to a second input based on a second activity metric to generate a second filtered result, the second filter being different than the first filter, the second input being one of a pre-deblocked image, or a prediction image, or a quantized prediction error image, or combinations thereof, and the first input and the second input corresponding to intermediate video block data for a single video block produced during a video decoding process; and
generating a filtered image based on the first filtered result and the second filtered result.

10. The method of claim 9, wherein the second filter is from the first set of filters.

11. The method of claim 9, wherein the second filter is from a second set of filters.

12. A device for decoding video data, the device comprising:
a filter unit configured to:
receive a syntax element, the syntax element indicating that the coefficients of a filter comprise at least one non-zero coefficient and a second value for the syntax element indicating that the coefficients of the filter comprise all zero coefficients;
based on the value of the syntax element being set to the second value, reconstruct the filter with all zero coefficients;
apply a first filter from a set of filters to a first input based on a first activity metric to generate a first filtered result, the first input comprising a post-deblocked reconstructed image, the set of filters including the filter with all zero coefficients;
and

a memory configured to store a filtered image based on the first filtered result.

13. The device of claim 12, wherein the first activity metric comprises a sum-modified Laplacian value.

14. The device of claim 13, wherein the sum-modified Laplacian value comprises var(i,j) defined approximately according to the following equation:




  
    var
    ⁡
    
      (
      
        i
        ,
        j
      
      )
    
  
  =
  
    
      
        ∑
        
          k
          =
          
            -
            K
          
        
        K
      
      ⁢
      
        ∑
        
          l
          =
          
            -
            L
          
        
        L
      
    
    |
    
      
        2
        ⁢
        
          R
          ⁡
          
            (
            
              
                i
                +
                k
              
              ,
              
                j
                +
                l
              
            
            )
          
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              -
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              +
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
    
    |
    
      +
      
        |
        
          
            2
            ⁢
            
              R
              ⁡
              
                (
                
                  
                    i
                    +
                    k
                  
                  ,
                  
                    j
                    +
                    l
                  
                
                )
              
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  -
                  1
                
              
              )
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  +
                  1
                
              
              )
            
          
        
        |
      
    
  




wherein k represents a value of a summation from −K to K and 1 represents a value of a summation from −L to L for a two-dimensional window that spans from −K to K and −L to L, wherein i and j represent pixel coordinates of the pixel data, R(i,j) represents a given pixel value at coordinates i and j, and var(i,j) is the first activity metric.

15. The device of claim 12, the first activity metric being an activity metric of the post-deblocked reconstructed image.

16. The device of claim 12, wherein a first range of values for the first activity metric is indexed to the first filter and a different range of values for the first activity metric is indexed to a different filter of the first set of filters.

17. The device of claim 12, the filter unit being further configured to:
in response to the value of the syntax element being set to the first value, reconstruct the coefficients of the filter based on additional information received from a video encoder, wherein the received additional information identifies the coefficients of the filter.

18. The device of claim 12, wherein the syntax element is a single bit.

19. The device of claim 12, wherein the syntax element is part of a header of a series of video blocks.

20. The device of claim 12, the filter unit being further configured to:
apply a second filter to a second input based on a second activity metric to generate a second filtered result, the second filter being different than the first filter, the second input being one of a pre-deblocked image, or a prediction image, or a quantized prediction error image, or combinations thereof, and the first input and the second input corresponding to intermediate video block data for a single video block produced during a video decoding process; and
generate a filtered image based on the first filtered result and the second filtered result.

21. The device of claim 20, the second filter being from the first set of filters.

22. The device of claim 20, the second filter being from a second set of filters.

23. An apparatus comprising:
means for receiving a syntax element, a first value for the syntax element indicating that coefficients of a filter comprise at least one non-zero coefficient and a second value for the syntax element indicating that the coefficients of the filter comprise all zero coefficients;
means for reconstructing, based on the value of the syntax element being set to the second value, the filter with all zero coefficients;
means for applying a first filter from a first set of filters to a first input based on a first activity metric to generate a first filtered result, wherein the first input comprises a post-deblocked reconstructed image, the set of filters including the filter with all zero coefficients;
and
means for generating a filtered image based on the first filtered result.

24. The apparatus of claim 23, wherein the first activity metric comprises a sum-modified Laplacian value.

25. The apparatus of claim 24, wherein the sum-modified Laplacian value comprises var(i,j) defined approximately according to the following equation:




  
    var
    ⁡
    
      (
      
        i
        ,
        j
      
      )
    
  
  =
  
    
      
        ∑
        
          k
          =
          
            -
            K
          
        
        K
      
      ⁢
      
        ∑
        
          l
          =
          
            -
            L
          
        
        L
      
    
    |
    
      
        2
        ⁢
        
          R
          ⁡
          
            (
            
              
                i
                +
                k
              
              ,
              
                j
                +
                l
              
            
            )
          
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              -
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              +
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
    
    |
    
      +
      
        |
        
          
            2
            ⁢
            
              R
              ⁡
              
                (
                
                  
                    i
                    +
                    k
                  
                  ,
                  
                    j
                    +
                    l
                  
                
                )
              
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  -
                  1
                
              
              )
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  +
                  1
                
              
              )
            
          
        
        |
      
    
  




wherein k represents a value of a summation from −K to K and 1 represents a value of a summation from −L to L for a two-dimensional window that spans from −K to K and −L to L, wherein i and j represent pixel coordinates of the pixel data, R(i,j) represents a given pixel value at coordinates i and j, and var(i,j) is the first activity metric.

26. The apparatus of claim 23, the first activity metric being an activity metric of the post-deblocked reconstructed image, and wherein the second activity metric is an activity metric of the second input.

27. The apparatus of claim 23, wherein a first range of values for the first activity metric is indexed to the first filter and a different range of values for the first activity metric is indexed to a different filter of the set of filters.

28. The apparatus of claim 23, the apparatus comprising a video decoding device, and the apparatus further comprising:
means for reconstructing the coefficients of the filter based on additional information received from a video encoder in response to the value of the syntax element being set to the first value, wherein the received additional information identifies the coefficients of the filter.

29. The apparatus of claim 23, wherein the syntax element is a single bit.

30. The apparatus of claim 23, wherein the syntax element is part of a header of a series of video blocks.

31. The apparatus of claim 23, further comprising:
means for applying a second filter to a second input based on a second activity metric to generate a second filtered result, the second filter being different than the first filter, the second input being one of a pre-deblocked image, or a prediction image, or a quantized prediction error image, or combinations thereof, and the first input and the second input corresponding to intermediate video block data for a single video block produced during a video decoding process; and
means for generating a filtered image based on the first filtered result and the second filtered result.

32. The apparatus of claim 31, the second filter being from the first set of filters.

33. The apparatus of claim 31, the second filter being from a second set of filters.

34. A non-transitory, computer readable storage medium tangibly storing one or more instructions, which when executed by one or more processors cause the one or more processors to:
receive a syntax element, the syntax element indicating that the coefficients of a filter comprise at least one non-zero coefficient and a second value for the syntax element indicating that the coefficients of the filter comprise all zero coefficients;
based on the value of the syntax element being set to the second value, reconstruct the filter with all zero coefficients;
apply a first filter from a set of filters to a first input based on a first activity metric to generate a first filtered result, the first input comprising a post-deblocked reconstructed image, the set of filters including the filter with all zero coefficients;
and
generate a filtered image based on the first filtered result.

35. The non-transitory computer readable storage medium of claim 34, wherein the first activity metric comprises a sum-modified Laplacian value.

36. The non-transitory computer readable storage medium of claim 35, wherein the sum-modified Laplacian value comprises var(i,j) defined approximately according to the following equation:




  
    var
    ⁡
    
      (
      
        i
        ,
        j
      
      )
    
  
  =
  
    
      
        ∑
        
          k
          =
          
            -
            K
          
        
        K
      
      ⁢
      
        ∑
        
          l
          =
          
            -
            L
          
        
        L
      
    
    |
    
      
        2
        ⁢
        
          R
          ⁡
          
            (
            
              
                i
                +
                k
              
              ,
              
                j
                +
                l
              
            
            )
          
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              -
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
      -
      
        R
        ⁡
        
          (
          
            
              i
              +
              k
              +
              1
            
            ,
            
              j
              +
              l
            
          
          )
        
      
    
    |
    
      +
      
        |
        
          
            2
            ⁢
            
              R
              ⁡
              
                (
                
                  
                    i
                    +
                    k
                  
                  ,
                  
                    j
                    +
                    l
                  
                
                )
              
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  -
                  1
                
              
              )
            
          
          -
          
            R
            ⁡
            
              (
              
                
                  i
                  +
                  k
                
                ,
                
                  j
                  +
                  l
                  +
                  1
                
              
              )
            
          
        
        |
      
    
  




wherein k represents a value of a summation from −K to K and 1 represents a value of a summation from −L to L for a two-dimensional window that spans from −K to K and −L to L, wherein i and j represent pixel coordinates of the pixel data, R(i,j) represents a given pixel value at coordinates i and j, and var(i,j) is the first activity metric.

37. The non-transitory computer readable storage medium of claim 34, the first activity metric being an activity metric of the post-deblocked reconstructed image.

38. The non-transitory computer readable storage medium of claim 34, wherein a first range of values of the first activity metric is indexed to the first filter and a different range of values for the first activity metric is indexed to a different filter of the first set of filters.

39. The non-transitory computer readable storage medium of claim 34, the computer readable storage medium being part of a video decoding device, and the computer readable storage medium tangibly storing additional instructions, which when executed by the one or more processors cause the one or more processors to:
in response to the value of the syntax element being set to the first value, reconstruct the coefficients of the filter based on additional information received from a video encoder, wherein the received additional information identifies the coefficients of the filter.

40. The non-transitory computer readable storage medium of claim 34, wherein the syntax element is a single bit.

41. The non-transitory computer readable storage medium of claim 34, wherein the syntax element is part of a header of a series of video blocks.

42. The non-transitory computer readable storage medium of claim 34, tangibly storing additional instructions, which when executed by the one or more processors cause the one or more processors to:
apply a second filter to a second input based on a second activity metric to generate a second filtered result, the second filter being different than the first filter, the second input being one of a pre-deblocked image, or a prediction image, or a quantized prediction error image, or combinations thereof, and the first input and the second input corresponding to intermediate video block data for a single video block produced during a video decoding process; and
generate a filtered image based on the first filtered result and the second filtered result.

43. The non-transitory computer readable storage medium of claim 42, the second filter being from the set of filters.

44. The non-transitory computer readable storage medium of claim 42, the second filter being from a second set of filters.

45. A method of encoding video data, the method comprising:
generating a filter syntax element, a first value for the filter syntax element indicating that coefficients of a filter comprise at least one non-zero coefficient and a second value for the filter syntax element indicating that the coefficients of the filter comprise all zero coefficients;
based on the filter syntax element being set to the first value, generating for inclusion in an encoded bitstream the filter syntax element and additional information identifying the coefficients of the filter;
applying a first filter from a first set of filters to a first input based on a first activity metric to generate a first filtered result, the first input comprising a post-deblocked reconstructed image, the set of filters including the filter with all zero coefficients; and
generating a filtered image based on the first filtered result.

46. The method of claim 45, further comprising:
in response to the filter syntax element being set to the second value, generating for inclusion in the encoded bitstream, the filter syntax element without additional information identifying the coefficients of the filter.

47. The method of claim 45, the method further comprising:
applying a second filter to a second input based on a second activity metric to generate a second filtered result, the second filter being different than the first filter, the second input being one of a pre-deblocked image, or a prediction image, or a quantized prediction error image, or combinations thereof, and the first input and the second input corresponding to intermediate video block data for a single video block produced during a video encoding process; and
generating a filtered image based on the first filtered result and the second filtered result.