Patent Description:
<CIT> describes a system and method that receives video data and its corresponding alpha channel data using a single stream or file, each of the video data and alpha channel data in the same format, and decompresses each set of data using a single decompression algorithm. <NPL>describes <NUM> experiments addressing content based coding and access.

This application relates to encoding and decoding of image data, video stream data, or both for transmission or storage. Disclosed herein are aspects of systems, methods, and apparatuses for encoding and decoding using alpha channel prediction.

An aspect is a method for image coding using alpha channel prediction. Image coding using alpha channel prediction may include generating a reconstructed image using alpha channel prediction and outputting the reconstructed image. Generating the reconstructed image using alpha channel prediction may include obtaining reconstructed color channel values for a current pixel of the current image expressed with reference to first color space, obtaining color space converted color channel values for the current pixel by converting the reconstructed color channel values to a second color space, obtaining an alpha channel lower bound for an alpha channel value for the current pixel using the color space converted color channel values, generating a candidate predicted alpha value for the current pixel, obtaining an adjusted predicted alpha value for the current pixel using the candidate predicted alpha value and the alpha channel lower bound, obtaining a decoded residual alpha value and generating a reconstructed alpha value for the current pixel as a sum of the adjusted predicted alpha value and the decoded residual alpha value; generating a reconstructed pixel for the current pixel using the reconstructed alpha value, and including the reconstructed pixel in the reconstructed image.

Another aspect is a method for image coding using alpha channel prediction. Image coding using alpha channel prediction may include generating an encoded image using alpha channel prediction and outputting an output bitstream. Generating the encoded image using alpha channel prediction may include identifying a current pixel from an input image, wherein the current pixel includes input color channel values, wherein the input color channel values are expressed with reference to first color space, and wherein the input color channel values include an input alpha channel value, obtaining pre-multiplied color channel values for the pixel using the input color channel values, obtaining reconstructed color values for the pixel using the pre-multiplied color channel values, wherein the reconstructed color channel values are expressed with reference to second color space, obtaining color space converted color channel values for the current pixel by color space converting the reconstructed color channel values to the first color space, obtaining an alpha channel lower bound for a reconstructed alpha channel value for the current pixel using the color space converted color channel values, generating a candidate predicted alpha value for the current pixel, obtaining an adjusted predicted alpha value for the current pixel using the candidate predicted alpha value and the alpha channel lower bound, obtaining a residual alpha value as a difference of subtracting the adjusted predicted alpha value from the input alpha channel value, and including the residual alpha value in an output bitstream.

Another aspect is an apparatus including a processor configured to perform the above-metioned methods.

The description herein makes reference to the accompanying drawings wherein like reference numerals refer to like parts throughout the several views unless otherwise noted or otherwise clear from context.

Image and video compression schemes may include breaking an image, or frame, into smaller portions, such as blocks, and generating an output bitstream using techniques to minimize the bandwidth utilization of the information included for each block in the output. In some implementations, the information included for each block in the output may be limited by reducing spatial redundancy, reducing temporal redundancy, or a combination thereof. For example, temporal or spatial redundancies may be reduced by predicting a frame, or a portion thereof, based on information available to both the encoder and decoder, and including information representing a difference, or residual, between the predicted frame and the original frame in the encoded bitstream. The residual information may be further compressed by transforming the residual information into transform coefficients, quantizing the transform coefficients, and entropy coding the quantized transform coefficients. Other coding information, such as motion information, may be included in the encoded bitstream, which may include transmitting differential information based on predictions of the encoding information, which may be entropy coded to further reduce the corresponding bandwidth utilization. An encoded bitstream can be decoded to reconstruct the blocks and the source images from the limited information. In some implementations, the accuracy, efficiency, or both, of coding a block using either inter-prediction or intra-prediction may be limited.

Implementations of coding, such as encoding or decoding, using alpha channel prediction may include using previously reconstructed alpha pre-multiplied RGB color values to obtain an alpha channel lower bound, and using the alpha channel lower bound to improve the accuracy of a predictor for the alpha channel.

<FIG> is a diagram of a computing device <NUM> in accordance with implementations of this disclosure. The computing device <NUM> shown includes a memory <NUM>, a processor <NUM>, a user interface (UI) <NUM>, an electronic communication unit <NUM>, a sensor <NUM>, a power source <NUM>, and a bus <NUM>. As used herein, the term "computing device" includes any unit, or a combination of units, capable of performing any method, or any portion or portions thereof, disclosed herein.

The computing device <NUM> may be a stationary computing device, such as a personal computer (PC), a server, a workstation, a minicomputer, or a mainframe computer; or a mobile computing device, such as a mobile telephone, a personal digital assistant (PDA), a laptop, or a tablet PC. Although shown as a single unit, any one element or elements of the computing device <NUM> can be integrated into any number of separate physical units. For example, the user interface <NUM> and processor <NUM> can be integrated in a first physical unit and the memory <NUM> can be integrated in a second physical unit.

The memory <NUM> can include any non-transitory computer-usable or computer-readable medium, such as any tangible device that can, for example, contain, store, communicate, or transport data <NUM>, instructions <NUM>, an operating system <NUM>, or any information associated therewith, for use by or in connection with other components of the computing device <NUM>. The non-transitory computer-usable or computer-readable medium can be, for example, a solid state drive, a memory card, removable media, a read-only memory (ROM), a random-access memory (RAM), any type of disk including a hard disk, a floppy disk, an optical disk, a magnetic or optical card, an application-specific integrated circuits (ASICs), or any type of non-transitory media suitable for storing electronic information, or any combination thereof.

Although shown a single unit, the memory <NUM> may include multiple physical units, such as one or more primary memory units, such as random-access memory units, one or more secondary data storage units, such as disks, or a combination thereof. For example, the data <NUM>, or a portion thereof, the instructions <NUM>, or a portion thereof, or both, may be stored in a secondary storage unit and may be loaded or otherwise transferred to a primary storage unit in conjunction with processing the respective data <NUM>, executing the respective instructions <NUM>, or both. In some implementations, the memory <NUM>, or a portion thereof, may be removable memory.

The data <NUM> can include information, such as input audio data, encoded audio data, decoded audio data, or the like. The instructions <NUM> can include directions, such as code, for performing any method, or any portion or portions thereof, disclosed herein. The instructions <NUM> can be realized in hardware, software, or any combination thereof. For example, the instructions <NUM> may be implemented as information stored in the memory <NUM>, such as a computer program, that may be executed by the processor <NUM> to perform any of the respective methods, algorithms, aspects, or combinations thereof, as described herein.

Although shown as included in the memory <NUM>, in some implementations, the instructions <NUM>, or a portion thereof, may be implemented as a special purpose processor, or circuitry, that can include specialized hardware for carrying out any of the methods, algorithms, aspects, or combinations thereof, as described herein. Portions of the instructions <NUM> can be distributed across multiple processors on the same machine or different machines or across a network such as a local area network, a wide area network, the Internet, or a combination thereof.

The processor <NUM> can include any device or system capable of manipulating or processing a digital signal or other electronic information now-existing or hereafter developed, including optical processors, quantum processors, molecular processors, or a combination thereof. For example, the processor <NUM> can include a special purpose processor, a central processing unit (CPU), a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessor in association with a DSP core, a controller, a microcontroller, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a programmable logic array, programmable logic controller, microcode, firmware, any type of integrated circuit (IC), a state machine, or any combination thereof. As used herein, the term "processor" includes a single processor or multiple processors.

The user interface <NUM> can include any unit capable of interfacing with a user, such as a virtual or physical keypad, a touchpad, a display, a touch display, a speaker, a microphone, a video camera, a sensor, or any combination thereof. For example, the user interface <NUM> may be an audio-visual display device, and the computing device <NUM> may present audio, such as decoded audio, using the user interface <NUM> audio-visual display device, such as in conjunction with displaying video, such as decoded video. Although shown as a single unit, the user interface <NUM> may include one or more physical units. For example, the user interface <NUM> may include an audio interface for performing audio communication with a user, and a touch display for performing visual and touch-based communication with the user.

The electronic communication unit <NUM> can transmit, receive, or transmit and receive signals via a wired or wireless electronic communication medium <NUM>, such as a radio frequency (RF) communication medium, an ultraviolet (UV) communication medium, a visible light communication medium, a fiber optic communication medium, a wireline communication medium, or a combination thereof. For example, as shown, the electronic communication unit <NUM> is operatively connected to an electronic communication interface <NUM>, such as an antenna, configured to communicate via wireless signals.

Although the electronic communication interface <NUM> is shown as a wireless antenna in <FIG>, the electronic communication interface <NUM> can be a wireless antenna, as shown, a wired communication port, such as an Ethernet port, an infrared port, a serial port, or any other wired or wireless unit capable of interfacing with a wired or wireless electronic communication medium <NUM>. Although <FIG> shows a single electronic communication unit <NUM> and a single electronic communication interface <NUM>, any number of electronic communication units and any number of electronic communication interfaces can be used.

The sensor <NUM> may include, for example, an audio-sensing device, a visible light-sensing device, a motion sensing device, or a combination thereof. For example, 100the sensor <NUM> may include a sound-sensing device, such as a microphone, or any other sound-sensing device now existing or hereafter developed that can sense sounds in the proximity of the computing device <NUM>, such as speech or other utterances, made by a user operating the computing device <NUM>. In another example, the sensor <NUM> may include a camera, or any other image-sensing device now existing or hereafter developed that can sense an image such as the image of a user operating the computing device. Although a single sensor <NUM> is shown, the computing device <NUM> may include a number of sensors <NUM>. For example, the computing device <NUM> may include a first camera oriented with a field of view directed toward a user of the computing device <NUM> and a second camera oriented with a field of view directed away from the user of the computing device <NUM>.

The power source <NUM> can be any suitable device for powering the computing device <NUM>. For example, the power source <NUM> can include a wired external power source interface; one or more dry cell batteries, such as nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion); solar cells; fuel cells; or any other device capable of powering the computing device <NUM>. Although a single power source <NUM> is shown in <FIG>, the computing device <NUM> may include multiple power sources <NUM>, such as a battery and a wired external power source interface.

Although shown as separate units, the electronic communication unit <NUM>, the electronic communication interface <NUM>, the user interface <NUM>, the power source <NUM>, or portions thereof, may be configured as a combined unit. For example, the electronic communication unit <NUM>, the electronic communication interface <NUM>, the user interface <NUM>, and the power source <NUM> may be implemented as a communications port capable of interfacing with an external display device, providing communications, power, or both.

One or more of the memory <NUM>, the processor <NUM>, the user interface <NUM>, the electronic communication unit <NUM>, the sensor <NUM>, or the power source <NUM>, may be operatively coupled via a bus <NUM>. Although a single bus <NUM> is shown in <FIG>, a computing device <NUM> may include multiple buses. For example, the memory <NUM>, the processor <NUM>, the user interface <NUM>, the electronic communication unit <NUM>, the sensor <NUM>, and the bus <NUM> may receive power from the power source <NUM> via the bus <NUM>. In another example, the memory <NUM>, the processor <NUM>, the user interface <NUM>, the electronic communication unit <NUM>, the sensor <NUM>, the power source <NUM>, or a combination thereof, may communicate data, such as by sending and receiving electronic signals, via the bus <NUM>.

Although not shown separately in <FIG>, one or more of the processor <NUM>, the user interface <NUM>, the electronic communication unit <NUM>, the sensor <NUM>, or the power source <NUM> may include internal memory, such as an internal buffer or register. For example, the processor <NUM> may include internal memory (not shown) and may read data <NUM> from the memory <NUM> into the internal memory (not shown) for processing.

Although shown as separate elements, the memory <NUM>, the processor <NUM>, the user interface <NUM>, the electronic communication unit <NUM>, the sensor <NUM>, the power source <NUM>, and the bus <NUM>, or any combination thereof can be integrated in one or more electronic units, circuits, or chips.

<FIG> is a diagram of a computing and communications system <NUM> in accordance with implementations of this disclosure. The computing and communications system <NUM> shown includes computing and communication devices 100A, 100B, 100C, access points 210A, 210B, and a network <NUM>. For example, the computing and communication system <NUM> can be a multiple access system that provides communication, such as voice, audio, data, video, messaging, broadcast, or a combination thereof, to one or more wired or wireless communicating devices, such as the computing and communication devices 100A, 100B, 100C. Although, for simplicity, <FIG> shows three computing and communication devices 100A, 100B, 100C, two access points 210A, 210B, and one network <NUM>, any number of computing and communication devices, access points, and networks can be used.

A computing and communication device 100A, 100B, 100C can be, for example, a computing device, such as the computing device <NUM> shown in <FIG>. For example, the computing and communication devices 100A, 100B may be user devices, such as a mobile computing device, a laptop, a thin client, or a smartphone, and the computing and communication device 100C may be a server, such as a mainframe or a cluster. Although the computing and communication device 100A and the computing and communication device 100B are described as user devices, and the computing and communication device 100C is described as a server, any computing and communication device may perform some or all of the functions of a server, some or all of the functions of a user device, or some or all of the functions of a server and a user device. For example, the server computing and communication device 100C may receive, encode, process, store, transmit, or a combination thereof audio data and one or both of the computing and communication device 100A and the computing and communication device 100B may receive, decode, process, store, present, or a combination thereof the audio data.

Each computing and communication device 100A, 100B, 100C, which may include a user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a cellular telephone, a personal computer, a tablet computer, a server, consumer electronics, or any similar device, can be configured to perform wired or wireless communication, such as via the network <NUM>. For example, the computing and communication devices 100A, 100B, 100C can be configured to transmit or receive wired or wireless communication signals. Although each computing and communication device 100A, 100B, 100C is shown as a single unit, a computing and communication device can include any number of interconnected elements.

Each access point 210A, 210B can be any type of device configured to communicate with a computing and communication device 100A, 100B, 100C, a network <NUM>, or both via wired or wireless communication links 180A, 180B, 180C. For example, an access point 210A, 210B can include a base station, a base transceiver station (BTS), a Node-B, an enhanced Node-B (eNode-B), a Home Node-B (HNode-B), a wireless router, a wired router, a hub, a relay, a switch, or any similar wired or wireless device. Although each access point 210A, 210B is shown as a single unit, an access point can include any number of interconnected elements.

The network <NUM> can be any type of network configured to provide services, such as voice, data, applications, voice over internet protocol (VoIP), or any other communications protocol or combination of communications protocols, over a wired or wireless communication link. For example, the network <NUM> can be a local area network (LAN), wide area network (WAN), virtual private network (VPN), a mobile or cellular telephone network, the Internet, or any other means of electronic communication. The network can use a communication protocol, such as the transmission control protocol (TCP), the user datagram protocol (UDP), the internet protocol (IP), the real-time transport protocol (RTP) the HyperText Transport Protocol (HTTP), or a combination thereof.

The computing and communication devices 100A, 100B, 100C can communicate with each other via the network <NUM> using one or more a wired or wireless communication links, or via a combination of wired and wireless communication links. For example, as shown the computing and communication devices 100A, 100B can communicate via wireless communication links 180A, 180B, and computing and communication device 100C can communicate via a wired communication link 180C. Any of the computing and communication devices 100A, 100B, 100C may communicate using any wired or wireless communication link, or links. For example, a first computing and communication device 100A can communicate via a first access point 210A using a first type of communication link, a second computing and communication device 100B can communicate via a second access point 210B using a second type of communication link, and a third computing and communication device 100C can communicate via a third access point (not shown) using a third type of communication link. Similarly, the access points 210A, 210B can communicate with the network <NUM> via one or more types of wired or wireless communication links 230A, 230B. Although <FIG> shows the computing and communication devices 100A, 100B, 100C in communication via the network <NUM>, the computing and communication devices 100A, 100B, 100C can communicate with each other via any number of communication links, such as a direct wired or wireless communication link.

In some implementations, communications between one or more of the computing and communication device 100A, 100B, 100C may omit communicating via the network <NUM> and may include transferring data via another medium (not shown), such as a data storage device. For example, the server computing and communication device 100C may store audio data, such as encoded audio data, in a data storage device, such as a portable data storage unit, and one or both of the computing and communication device 100A or the computing and communication device 100B may access, read, or retrieve the stored audio data from the data storage unit, such as by physically disconnecting the data storage device from the server computing and communication device 100C and physically connecting the data storage device to the computing and communication device 100A or the computing and communication device 100B.

Other implementations of the computing and communications system <NUM> are possible. For example, in an implementation, the network <NUM> can be an ad-hoc network and can omit one or more of the access points 210A, 210B. The computing and communications system <NUM> may include devices, units, or elements not shown in <FIG>. For example, the computing and communications system <NUM> may include many more communicating devices, networks, and access points.

<FIG> is a diagram of a video stream <NUM> for use in encoding and decoding in accordance with implementations of this disclosure. A video stream <NUM>, such as a video stream captured by a video camera or a video stream generated by a computing device, may include a video sequence <NUM>. The video sequence <NUM> may include a sequence of adjacent frames <NUM>. Although three adjacent frames <NUM> are shown, the video sequence <NUM> can include any number of adjacent frames <NUM>.

Each frame <NUM> from the adjacent frames <NUM> may represent a single image from the video stream. Although not shown in <FIG>, a frame <NUM> may include one or more segments, tiles, or planes, which may be coded, or otherwise processed, independently, such as in parallel. A frame <NUM> may include one or more tiles <NUM>. Each of the tiles <NUM> may be a rectangular region of the frame that can be coded independently. Each of the tiles <NUM> may include respective blocks <NUM>. Although not shown in <FIG>, a block can include pixels. For example, a block can include a <NUM>×<NUM> group of pixels, an <NUM>×<NUM> group of pixels, an <NUM>×<NUM> group of pixels, or any other group of pixels. Unless otherwise indicated herein, the term 'block' can include a superblock, a macroblock, a segment, a slice, or any other portion of a frame. A frame, a block, a pixel, or a combination thereof can include display information, such as luminance information, chrominance information, or any other information that can be used to store, modify, communicate, or display the video stream or a portion thereof.

<FIG> is a block diagram of an encoder <NUM> in accordance with implementations of this disclosure. Encoder <NUM> can be implemented in a device, such as the computing device <NUM> shown in <FIG> or the computing and communication devices 100A, 100B, 100C shown in <FIG>, as, for example, a computer software program stored in a data storage unit, such as the memory <NUM> shown in <FIG>. The computer software program can include machine instructions that may be executed by a processor, such as the processor <NUM> shown in <FIG>, and may cause the device to encode video data as described herein. The encoder <NUM> can be implemented as specialized hardware included, for example, in computing device <NUM>.

The encoder <NUM> can encode an input video stream <NUM>, such as the video stream <NUM> shown in <FIG>, to generate an encoded (compressed) bitstream <NUM>. In some implementations, the encoder <NUM> may include a forward path for generating the compressed bitstream <NUM>. The forward path may include an intralinter prediction unit <NUM>, a transform unit <NUM>, a quantization unit <NUM>, an entropy encoding unit <NUM>, or any combination thereof. In some implementations, the encoder <NUM> may include a reconstruction path (indicated by the broken connection lines) to reconstruct a frame for encoding of further blocks. The reconstruction path may include a dequantization unit <NUM>, an inverse transform unit <NUM>, a reconstruction unit <NUM>, a filtering unit <NUM>, or any combination thereof. Other structural variations of the encoder <NUM> can be used to encode the video stream <NUM>.

For encoding the video stream <NUM>, each frame within the video stream <NUM> can be processed in units of blocks. Thus, a current block may be identified from the blocks in a frame, and the current block may be encoded.

At the intralinter prediction unit <NUM>, the current block can be encoded using either intra-frame prediction, which may be within a single frame, or inter-frame prediction, which may be from frame to frame. Intra-prediction may include generating a prediction block from samples in the current frame that have been previously encoded and reconstructed. Inter-prediction may include generating a prediction block from samples in one or more previously constructed reference frames. Generating a prediction block for a current block in a current frame may include performing motion estimation to generate a motion vector indicating an appropriate reference portion of the reference frame.

The intralinter prediction unit <NUM> may subtract the prediction block from the current block (raw block) to produce a residual block. The transform unit <NUM> may perform a block-based transform, which may include transforming the residual block into transform coefficients in, for example, the frequency domain. Examples of block-based transforms include the Karhunen-Loève Transform (KLT), the Discrete Cosine Transform (DCT), the Singular Value Decomposition Transform (SVD), and the Asymmetric Discrete Sine Transform (ADST). In an example, the DCT may include transforming a block into the frequency domain. The DCT may include using transform coefficient values based on spatial frequency, with the lowest frequency (i.e. DC) coefficient at the top-left of the matrix and the highest frequency coefficient at the bottom-right of the matrix.

The quantization unit <NUM> may convert the transform coefficients into discrete quantum values, which may be referred to as quantized transform coefficients or quantization levels. The quantized transform coefficients can be entropy encoded by the entropy encoding unit <NUM> to produce entropy-encoded coefficients. Entropy encoding can include using a probability distribution metric. The entropy-encoded coefficients and information used to decode the block, which may include the type of prediction used, motion vectors, and quantizer values, can be output to the compressed bitstream <NUM>. The compressed bitstream <NUM> can be formatted using various techniques, such as run-length encoding (RLE) and zero-run coding.

The reconstruction path can be used to maintain reference frame synchronization between the encoder <NUM> and a corresponding decoder, such as the decoder <NUM> shown in <FIG>. The reconstruction path may be similar to the decoding process discussed below and may include decoding the encoded frame, or a portion thereof, which may include decoding an encoded block, which may include dequantizing the quantized transform coefficients at the dequantization unit <NUM> and inverse transforming the dequantized transform coefficients at the inverse transform unit <NUM> to produce a derivative residual block. The reconstruction unit <NUM> may add the prediction block generated by the intralinter prediction unit <NUM> to the derivative residual block to create a decoded block. The filtering unit <NUM> can be applied to the decoded block to generate a reconstructed block, which may reduce distortion, such as blocking artifacts. Although one filtering unit <NUM> is shown in <FIG>, filtering the decoded block may include loop filtering, deblocking filtering, or other types of filtering or combinations of types of filtering. The reconstructed block may be stored or otherwise made accessible as a reconstructed block, which may be a portion of a reference frame, for encoding another portion of the current frame, another frame, or both, as indicated by the broken line at <NUM>. Coding information, such as deblocking threshold index values, for the frame may be encoded, included in the compressed bitstream <NUM>, or both, as indicated by the broken line at <NUM>.

Other variations of the encoder <NUM> can be used to encode the compressed bitstream <NUM>. For example, a non-transform-based encoder <NUM> can quantize the residual block directly without the transform unit <NUM>. In some implementations, the quantization unit <NUM> and the dequantization unit <NUM> may be combined into a single unit.

<FIG> is a block diagram of a decoder <NUM> in accordance with implementations of this disclosure. The decoder <NUM> can be implemented in a device, such as the computing device <NUM> shown in <FIG> or the computing and communication devices 100A, 100B, 100C shown in <FIG>, as, for example, a computer software program stored in a data storage unit, such as the memory <NUM> shown in <FIG>. The computer software program can include machine instructions that may be executed by a processor, such as the processor <NUM> shown in <FIG>, and may cause the device to decode video data as described herein. The decoder <NUM> can be implemented as specialized hardware included, for example, in computing device <NUM>.

The decoder <NUM> may receive a compressed bitstream <NUM>, such as the compressed bitstream <NUM> shown in <FIG>, and may decode the compressed bitstream <NUM> to generate an output video stream <NUM>. The decoder <NUM> may include an entropy decoding unit <NUM>, a dequantization unit <NUM>, an inverse transform unit <NUM>, an intralinter prediction unit <NUM>, a reconstruction unit <NUM>, a filtering unit <NUM>, or any combination thereof. Other structural variations of the decoder <NUM> can be used to decode the compressed bitstream <NUM>.

The entropy decoding unit <NUM> may decode data elements within the compressed bitstream <NUM> using, for example, Context Adaptive Binary Arithmetic Decoding, to produce a set of quantized transform coefficients. The dequantization unit <NUM> can dequantize the quantized transform coefficients, and the inverse transform unit <NUM> can inverse transform the dequantized transform coefficients to produce a derivative residual block, which may correspond to the derivative residual block generated by the inverse transform unit <NUM> shown in <FIG>. Using header information decoded from the compressed bitstream <NUM>, the intralinter prediction unit <NUM> may generate a prediction block corresponding to the prediction block created in the encoder <NUM>. At the reconstruction unit <NUM>, the prediction block can be added to the derivative residual block to create a decoded block. The filtering unit <NUM> can be applied to the decoded block to reduce artifacts, such as blocking artifacts, which may include loop filtering, deblocking filtering, or other types of filtering or combinations of types of filtering, and which may include generating a reconstructed block, which may be output as the output video stream <NUM>.

Other variations of the decoder <NUM> can be used to decode the compressed bitstream <NUM>. For example, the decoder <NUM> can produce the output video stream <NUM> without a deblocking filtering unit.

<FIG> is a block diagram of a representation of a portion <NUM> of a frame, such as the frame <NUM> shown in <FIG>, in accordance with implementations of this disclosure. As shown, the portion <NUM> of the frame includes four <NUM>×<NUM> blocks <NUM>, in two rows and two columns in a matrix or Cartesian plane. In some implementations, a <NUM>×<NUM> block may be a maximum coding unit, N=<NUM>. Each <NUM>×<NUM> block may include four <NUM>×<NUM> blocks <NUM>. Each <NUM>×<NUM> block may include four <NUM>×<NUM> blocks <NUM>. Each <NUM>×<NUM> block may include four <NUM>×<NUM> blocks <NUM>. Each <NUM>×<NUM> block <NUM> may include four <NUM>×<NUM> blocks <NUM>. Each <NUM>×<NUM> block <NUM> may include <NUM> pixels, which may be represented in four rows and four columns in each respective block in the Cartesian plane or matrix. The pixels may include information representing an image captured in the frame, such as luminance information, color information, and location information. In some implementations, a block, such as a <NUM>×<NUM> pixel block as shown, may include a luminance block <NUM>, which may include luminance pixels <NUM>; and two chrominance blocks <NUM>, <NUM>, such as a U or Cb chrominance block <NUM>, and a V or Cr chrominance block <NUM>. The chrominance blocks <NUM>, <NUM> may include chrominance pixels <NUM>. For example, the luminance block <NUM> may include <NUM>×<NUM> luminance pixels <NUM> and each chrominance block <NUM>, <NUM> may include <NUM>×<NUM> chrominance pixels <NUM> as shown. Although one arrangement of blocks is shown, any arrangement may be used. Although <FIG> shows N×N blocks, in some implementations, N×M blocks may be used. For example, <NUM>×<NUM> blocks, <NUM>×<NUM> blocks, <NUM>×<NUM> blocks, <NUM>×<NUM> blocks, or any other size blocks may be used. In some implementations, N×2N blocks, 2N×N blocks, or a combination thereof may be used.

In some implementations, video coding may include ordered block-level coding. Ordered block-level coding may include coding blocks of a frame in an order, such as raster-scan order, wherein blocks may be identified and processed starting with a block in the upper left corner of the frame, or portion of the frame, and proceeding along rows from left to right and from the top row to the bottom row, identifying each block in turn for processing. For example, the <NUM>×<NUM> block in the top row and left column of a frame may be the first block coded and the <NUM>×<NUM> block immediately to the right of the first block may be the second block coded. The second row from the top may be the second row coded, such that the <NUM>×<NUM> block in the left column of the second row may be coded after the <NUM>×<NUM> block in the rightmost column of the first row.

In some implementations, coding a block may include using quad-tree coding, which may include coding smaller block units within a block in raster-scan order. For example, the <NUM>×<NUM> block shown in the bottom left corner of the portion of the frame shown in <FIG>, may be coded using quad-tree coding wherein the top left <NUM>×<NUM> block may be coded, then the top right <NUM>×<NUM> block may be coded, then the bottom left <NUM>×<NUM> block may be coded, and then the bottom right <NUM>×<NUM> block may be coded. Each <NUM>×<NUM> block may be coded using quad-tree coding wherein the top left <NUM>×<NUM> block may be coded, then the top right <NUM>×<NUM> block may be coded, then the bottom left <NUM>×<NUM> block may be coded, and then the bottom right <NUM>×<NUM> block may be coded. Each <NUM>×<NUM> block may be coded using quad-tree coding wherein the top left <NUM>×<NUM> block may be coded, then the top right <NUM>×<NUM> block may be coded, then the bottom left <NUM>×<NUM> block may be coded, and then the bottom right <NUM>×<NUM> block may be coded. Each <NUM>×<NUM> block may be coded using quad-tree coding wherein the top left <NUM>×<NUM> block may be coded, then the top right <NUM>×<NUM> block may be coded, then the bottom left <NUM>×<NUM> block may be coded, and then the bottom right <NUM>×<NUM> block may be coded. In some implementations, <NUM>×<NUM> blocks may be omitted for a <NUM>×<NUM> block, and the <NUM>×<NUM> block may be coded using quad-tree coding wherein the top left <NUM>×<NUM> block may be coded, then the other <NUM>×<NUM> blocks in the <NUM>×<NUM> block may be coded in raster-scan order.

In some implementations, video coding may include compressing the information included in an original, or input, frame by, for example, omitting some of the information in the original frame from a corresponding encoded frame. For example, coding may include reducing spectral redundancy, reducing spatial redundancy, reducing temporal redundancy, or a combination thereof.

In some implementations, reducing spectral redundancy may include using a color model based on a luminance component (Y) and two chrominance components (U and V or Cb and Cr), which may be referred to as the YUV or YCbCr color model, or color space. Using the YUV color model may include using a relatively large amount of information to represent the luminance component of a portion of a frame and using a relatively small amount of information to represent each corresponding chrominance component for the portion of the frame. For example, a portion of a frame may be represented by a high-resolution luminance component, which may include a <NUM>×<NUM> block of pixels, and by two lower resolution chrominance components, each of which represents the portion of the frame as an <NUM>×<NUM> block of pixels. A pixel may indicate a value, for example, a value in the range from <NUM> to <NUM>, and may be stored or transmitted using, for example, eight bits. Although this disclosure is described in reference to the YUV color model, any color model may be used.

In some implementations, reducing spatial redundancy may include transforming a block into the frequency domain using, for example, a discrete cosine transform (DCT). For example, a unit of an encoder, such as the transform unit <NUM> shown in <FIG>, may perform a DCT using transform coefficient values based on spatial frequency.

In some implementations, reducing temporal redundancy may include using similarities between frames to encode a frame using a relatively small amount of data based on one or more reference frames, which may be previously encoded, decoded, and reconstructed frames of the video stream. For example, a block or pixel of a current frame may be similar to a spatially corresponding block or pixel of a reference frame. In some implementations, a block or pixel of a current frame may be similar to block or pixel of a reference frame at a different spatial location and reducing temporal redundancy may include generating motion information indicating the spatial difference, or translation, between the location of the block or pixel in the current frame and corresponding location of the block or pixel in the reference frame.

In some implementations, reducing temporal redundancy may include identifying a portion of a reference frame that corresponds to a current block or pixel of a current frame. For example, a reference frame, or a portion of a reference frame, which may be stored in memory, may be searched to identify a portion for generating a prediction to use for encoding a current block or pixel of the current frame with maximal efficiency. For example, the search may identify a portion of the reference frame for which the difference in pixel values between the current block and a prediction block generated based on the portion of the reference frame is minimized and may be referred to as motion searching. In some implementations, the portion of the reference frame searched may be limited. For example, the portion of the reference frame searched, which may be referred to as the search area, may include a limited number of rows of the reference frame. In an example, identifying the portion of the reference frame for generating a prediction may include calculating a cost function, such as a sum of absolute differences (SAD), between the pixels of portions of the search area and the pixels of the current block.

In some implementations, the spatial difference between the location of the portion of the reference frame for generating a prediction in the reference frame and the current block in the current frame may be represented as a motion vector. The difference in pixel values between the prediction block and the current block may be referred to as differential data, residual data, a prediction error, or as a residual block. In some implementations, generating motion vectors may be referred to as motion estimation, and a pixel of a current block may be indicated based on location using Cartesian coordinates as fx,y. Similarly, a pixel of the search area of the reference frame may be indicated based on location using Cartesian coordinates as rx,y. A motion vector (MV) for the current block may be determined based on, for example, a SAD between the pixels of the current frame and the corresponding pixels of the reference frame.

Although described herein with reference to matrix or Cartesian representation of a frame for clarity, a frame may be stored, transmitted, processed, or any combination thereof, in any data structure such that pixel values may be efficiently represented for a frame or image. For example, a frame may be stored, transmitted, processed, or any combination thereof, in a two-dimensional data structure such as a matrix as shown, or in a one-dimensional data structure, such as a vector array. In an implementation, a representation of the frame, such as a two-dimensional representation as shown, may correspond to a physical location in a rendering of the frame as an image. For example, a location in the top left corner of a block in the top left corner of the frame may correspond with a physical location in the top left corner of a rendering of the frame as an image.

In some implementations, block-based coding efficiency may be improved by partitioning input blocks into one or more prediction partitions, which may be rectangular, including square, partitions for prediction coding. In some implementations, video coding using prediction partitioning may include selecting a prediction partitioning scheme from among multiple candidate prediction partitioning schemes. For example, in some implementations, candidate prediction partitioning schemes for a <NUM>×<NUM> coding unit may include rectangular size prediction partitions ranging in sizes from <NUM>×<NUM> to <NUM>×<NUM>, such as <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, <NUM>×<NUM>, or <NUM>×<NUM>. In some implementations, video coding using prediction partitioning may include a full prediction partition search, which may include selecting a prediction partitioning scheme by encoding the coding unit using each available candidate prediction partitioning scheme and selecting the best scheme, such as the scheme that produces the least rate-distortion error.

In some implementations, encoding a video frame may include identifying a prediction partitioning scheme for encoding a current block, such as block <NUM>. In some implementations, identifying a prediction partitioning scheme may include determining whether to encode the block as a single prediction partition of maximum coding unit size, which may be <NUM>×<NUM> as shown, or to partition the block into multiple prediction partitions, which may correspond with the sub-blocks, such as the <NUM>×<NUM> blocks <NUM> the <NUM>×<NUM> blocks <NUM>, or the <NUM>×<NUM> blocks <NUM>, as shown, and may include determining whether to partition into one or more smaller prediction partitions. For example, a <NUM>×<NUM> block may be partitioned into four <NUM>×<NUM> prediction partitions. Three of the four <NUM>×<NUM> prediction partitions may be encoded as <NUM>×<NUM> prediction partitions and the fourth <NUM>×<NUM> prediction partition may be further partitioned into four <NUM>×<NUM> prediction partitions. Three of the four <NUM>×<NUM> prediction partitions may be encoded as <NUM>×<NUM> prediction partitions and the fourth <NUM>×<NUM> prediction partition may be further partitioned into four <NUM>×<NUM> prediction partitions, each of which may be encoded as an <NUM>×<NUM> prediction partition. In some implementations, identifying the prediction partitioning scheme may include using a prediction partitioning decision tree.

In some implementations, video coding for a current block may include identifying an optimal prediction coding mode from multiple candidate prediction coding modes, which may provide flexibility in handling video signals with various statistical properties and may improve the compression efficiency. For example, a video coder may evaluate each candidate prediction coding mode to identify the optimal prediction coding mode, which may be, for example, the prediction coding mode that minimizes an error metric, such as a rate-distortion cost, for the current block. In some implementations, the complexity of searching the candidate prediction coding modes may be reduced by limiting the set of available candidate prediction coding modes based on similarities between the current block and a corresponding prediction block. In some implementations, the complexity of searching each candidate prediction coding mode may be reduced by performing a directed refinement mode search. For example, metrics may be generated for a limited set of candidate block sizes, such as <NUM>×<NUM>, <NUM>×<NUM>, and <NUM>×<NUM>, the error metric associated with each block size may be in descending order, and additional candidate block sizes, such as <NUM>×<NUM> and <NUM>×<NUM> block sizes, may be evaluated.

In some implementations, block-based coding efficiency may be improved by partitioning a current residual block into one or more transform partitions, which may be rectangular, including square, partitions for transform coding. In some implementations, video coding using transform partitioning may include selecting a uniform transform partitioning scheme. For example, a current residual block, such as block <NUM>, may be a <NUM>×<NUM> block and may be transformed without partitioning using a <NUM>×<NUM> transform.

Although not expressly shown in <FIG>, a residual block may be transform partitioned using a uniform transform partitioning scheme. For example, a <NUM>×<NUM> residual block may be transform partitioned using a uniform transform partitioning scheme including four <NUM>×<NUM> transform blocks, using a uniform transform partitioning scheme including sixteen <NUM>×<NUM> transform blocks, using a uniform transform partitioning scheme including sixty-four <NUM>×<NUM> transform blocks, or using a uniform transform partitioning scheme including <NUM><NUM>×<NUM> transform blocks.

In some implementations, video coding using transform partitioning may include identifying multiple transform block sizes for a residual block using multiform transform partition coding. In some implementations, multiform transform partition coding may include recursively determining whether to transform a current block using a current block size transform or by partitioning the current block and multiform transform partition coding each partition. For example, the bottom left block <NUM> shown in <FIG> may be a <NUM>×<NUM> residual block, and multiform transform partition coding may include determining whether to code the current <NUM>×<NUM> residual block using a <NUM>×<NUM> transform or to code the <NUM>×<NUM> residual block by partitioning the <NUM>×<NUM> residual block into partitions, such as four <NUM>×<NUM> blocks <NUM>, and multiform transform partition coding each partition. In some implementations, determining whether to transform partition the current block may be based on comparing a cost for encoding the current block using a current block size transform to a sum of costs for encoding each partition using partition size transforms.

<FIG> is a flowchart diagram of an example of decoding using alpha channel prediction <NUM> in accordance with implementations of this disclosure. Decoding using alpha channel prediction <NUM> may be implemented in a decoder, such as the decoder <NUM> shown in <FIG>.

As shown in <FIG>, decoding using alpha channel prediction <NUM> includes identifying a current pixel at <NUM>, obtaining reconstructed color values at <NUM>, obtaining color space converted color values at <NUM>, obtaining an alpha channel lower bound at <NUM>, generating a predicted alpha channel value at <NUM>, obtaining an adjusted predicted alpha channel value at <NUM>, generating a reconstructed pixel at <NUM>, and outputting at <NUM>.

Although not expressly shown in <FIG>, decoding using alpha channel prediction <NUM> may include obtaining, such as receiving via a wired or wireless electronic communication medium, such as the network <NUM> shown in <FIG>, or reading from an electronic data storage medium, such as the memory <NUM> shown in <FIG>, at least a portion of an encoded bitstream. Decoding using alpha channel prediction <NUM> may include generating a reconstructed image. Generating the reconstructed image may include generating the reconstructed image using alpha channel prediction.

A current pixel may be identified at <NUM>. The current pixel may be a pixel of a current block of the current image, such as block <NUM> shown in <FIG>.

Reconstructed color channel values may be obtained for the current pixel at <NUM>. For example, obtaining the reconstructed color channel values for the current pixel may include obtaining the reconstructed color channel values for the current pixel expressed in a color model based on a luminance component (Y) and two chrominance components (U and V or Cb and Cr), which may be referred to as the YUV or YCbCr color model, or color space. Obtaining the reconstructed color channel values may include reconstructing the reconstructed color channel values using data, such as residual color channel values, decoded from the encoded bitstream. The data decoded from the encoded bitstream may be losslessly coded data or lossily coded data.

Color space converted color values for the pixel may be obtained at <NUM>. Obtaining the color space converted color values for the pixel may include color space conversion of the reconstructed color channel values, such as from the YUV color space to another color space, such as the RGB color space, which may include a red color channel (R), a green color channel (G), and a blue color channel (B).

An alpha channel lower bound may be obtained at <NUM>. In some implementations, the alpha channel lower bound may be an approximate alpha channel lower bound, such as in accordance with obtaining the alpha channel lower bound using lossily coded data. Obtaining the alpha channel lower bound may include obtaining a normalized red color channel value by dividing the red color channel value (R) by a defined maximum value for the red color channel (maxR). Obtaining the alpha channel lower bound may include obtaining a normalized green color channel value by dividing the green color channel value (G) by a defined maximum value for the green color channel (maxG). Obtaining the alpha channel lower bound may include obtaining a normalized blue color channel value by dividing the blue color channel value (B) by a defined maximum value for the blue color channel (maxB). Obtaining the alpha channel lower bound may include identifying a maximum value among the normalized red color channel value, the normalized green color channel value, and the normalized blue color channel value, identifying, as the approximate lower bound, a product of multiplying the maximum value among the normalized red color channel value, the normalized green color channel value, and the normalized blue color channel value by a defined maximum value for the alpha channel (maxA). Obtaining the alpha channel lower bound (minA) may be expressed as the following: <MAT>.

In some implementations, normalization may be omitted and obtaining the alpha channel lower bound (minA) may be expressed as minA = max(R, G, B).

A candidate predicted alpha channel value may be generated at <NUM>. Generating the candidate predicted alpha channel value (rpredA) may include using the alpha values of one or more reconstructed context pixels, such as pixels from blocks above, to the left of, and above and to the left of the current block. For example, the candidate predicted alpha channel value may be an average of the alpha channel values of the context pixels.

An adjusted predicted alpha channel value may be obtained at <NUM> using the candidate predicted alpha channel value identified at <NUM> and the alpha channel lower bound identified at <NUM>. Obtaining the adjusted predicted alpha channel value (predA) may be expressed as predA = max(rpredA, minA). In some implementations, obtaining the adjusted predicted alpha channel value (predA) may include using lossy compression based alpha channel lower bound adjustment (m), such as an adjustment based on the data lost in the lossy compression, such as based on a quantization level, and obtaining the adjusted predicted alpha channel value (predA) may be expressed as predA = max(rpredA, minA - m).

A reconstructed pixel may be generated at <NUM>. Generating the reconstructed pixel may include generating a reconstructed alpha channel value for the pixel. Generating the reconstructed alpha channel value may include obtaining, as the reconstructed alpha channel value, a sum of adding the adjusted predicted alpha channel value and a decoded residual alpha channel value for the pixel.

The reconstructed block pixel may be output at <NUM>. For example, the reconstructed pixel may be included in the reconstructed image, and the reconstructed image may be output, such as via the output stream <NUM> shown in <FIG>, such as for presentation to a user. Although not shown expressly in <FIG>, generating the reconstructed block or the reconstructed image may include filtering, such as the filtering shown at <NUM> in <FIG>.

<FIG> is a flowchart diagram of an example of encoding using alpha channel prediction <NUM> in accordance with implementations of this disclosure. Encoding using alpha channel prediction <NUM> may be implemented in an encoder, such as the encoder <NUM> shown in <FIG>. Encoding using alpha channel prediction <NUM> may be similar to decoding using alpha channel prediction <NUM> as shown in <FIG>, except as is described herein or as is otherwise clear from context.

As shown in <FIG>, encoding using alpha channel prediction <NUM> includes identifying a current pixel at <NUM>, obtaining pre-multiplied color values at <NUM>, obtaining reconstructed color values at <NUM>, obtaining color space converted color values at <NUM>, obtaining an alpha channel lower bound at <NUM>, generating a predicted alpha channel value at <NUM>, obtaining an adjusted predicted alpha channel value at <NUM>, generating a reconstructed pixel at <NUM>, and outputting at <NUM>.

Although not expressly shown in <FIG>, encoding using alpha channel prediction <NUM> may include obtaining a current image, which may be an input image.

Pre-multiplied color values for the pixel may be obtained at <NUM>. For example, the pixel may be expressed in the input image using the RGB color space, which may include a red color channel (R), a green color channel (G), and a blue color channel (B), and an alpha channel (A). Obtaining the pre-multiplied color values may include identifying a product of multiplying the red color channel value by the alpha channel value as the pre-multiplied red color channel value, identifying a product of multiplying the green color channel value by the alpha channel value as the pre-multiplied green color channel value, and identifying a product of multiplying the blue color channel value by the alpha channel value as the pre-multiplied blue color channel value. Obtaining the pre-multiplied color values may include obtaining a normalized alpha channel value and using the normalized alpha channel value to obtain the pre-multiplied color channel values. Obtaining the normalized alpha channel value may include obtain a result of dividing the input alpha channel value by a maximum alpha channel value. In some implementations, the input color channel values for the pixel may be pre-multiplied color values.

Reconstructed color channel values may be obtained for the current pixel at <NUM>. Although not shown separately in <FIG>, the pre-multiplied color values may be encoded, and the reconstructed color channel values may be obtained by decoding the encoded data for the pre-multiplied color values. Encoding the pre-multiplied color values may include color space conversion of the pre-multiplied color values, such as from the RGB color space to a color model based on a luminance component (Y) and two chrominance components (U and V or Cb and Cr), which may be referred to as the YUV or YCbCr color model, or color space. The encoded data may be losslessly coded data or lossily coded data.

Color space converted reconstructed color values for the pixel may be obtained at <NUM>. Obtaining the color space converted reconstructed color values for the pixel may include color space conversion of the reconstructed color channel values, such as from the YUV color space to another color space, such as the RGB color space.

An alpha channel lower bound, which may be an approximate lower bound, may be obtained at <NUM>. Obtaining the alpha channel lower bound may include obtaining a normalized red color channel value by dividing the red color space converted reconstructed color value (R) by a defined maximum value for the red color channel (maxR). Obtaining the alpha channel lower bound may include obtaining a normalized green color channel value by dividing the green color space converted reconstructed color value (G) by a defined maximum value for the green color channel (maxG). Obtaining the alpha channel lower bound may include obtaining a normalized blue color channel value by dividing the blue color space converted reconstructed color value (B) by a defined maximum value for the blue color channel (maxB). Obtaining the alpha channel lower bound may include identifying a maximum value among the normalized red color channel value, the normalized green color channel value, and the normalized blue color channel value, identifying, as the approximate lower bound, a product of multiplying the maximum value among the normalized red color channel value, the normalized green color channel value, and the normalized blue color channel value by a defined maximum value for the alpha channel (maxA). Obtaining the alpha channel lower bound (minA) may be expressed as the following: <MAT>.

In some implementations, normalization may be omitted and obtaining the alpha channel lower (minA) bound may be expressed as minA = max(R, G, B).

A predicted alpha channel value may be generated at <NUM>. Generating the predicted alpha channel value (rpredA) may include using the alpha values of one or more reconstructed context pixels, such as pixels from blocks above, to the left of, and above and to the left of the current block. For example, the predicted alpha channel value may be an average of the alpha channel values of the context pixels.

An adjusted predicted alpha channel value may be obtained at <NUM> using the candidate predicted alpha value identified at <NUM> and the alpha channel lower bound identified at <NUM>. Obtaining the adjusted predicted alpha channel value (predA) may be expressed as predA = max(rpredA, minA).

The encoded image data may be output at <NUM>. Although not shown separately in <FIG>, the adjusted predicted alpha channel value obtained at <NUM> may be subtracted from the input pixel alpha value to obtain a residual alpha value, and the residual alpha value may be included in the output bitstream.

In some implementations, the residual alpha value may be an alpha channel lower bound restricted residual alpha value wherein, for a residual alpha value less than the alpha channel lower bound, the alpha channel lower bound may be used as the residual alpha value. In some implementations, such as in accordance with obtaining the alpha channel lower bound using lossily coded data, an approximation of the alpha channel lower bound wherein, for a residual alpha value less than the approximation of the alpha channel lower bound, the approximation of the alpha channel lower bound may be used as the residual alpha value. The approximation of the alpha channel lower bound may be a product of multiplying the alpha channel lower bound by a defined approximation parameter, such as <NUM>.

As used herein, the terms "optimal", "optimized", "optimization", or other forms thereof, are relative to a respective context and are not indicative of absolute theoretic optimization unless expressly specified herein.

As used herein, the term "set" indicates a distinguishable collection or grouping of zero or more distinct elements or members that may be represented as a one-dimensional array or vector, except as expressly described herein or otherwise clear from context.

The words "example" or "exemplary" are used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as "example" or "exemplary" not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the words "example" or "exemplary" is intended to present concepts in a concrete fashion. As used in this application, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or". That is, unless specified otherwise, or clear from context, "X includes A or B" is intended to mean any of the natural inclusive permutations. That is, if X includes A; X includes B; or X includes both A and B, then "X includes A or B" is satisfied under any of the foregoing instances. In addition, the articles "a" and "an" as used in this application and the appended claims should generally be construed to mean "one or more" unless specified otherwise or clear from context to be directed to a singular form. Moreover, use of the term "an embodiment" or "one embodiment" or "an implementation" or "one implementation" throughout is not intended to mean the same embodiment or implementation unless described as such. As used herein, the terms "determine" and "identify", or any variations thereof, includes selecting, ascertaining, computing, looking up, receiving, determining, establishing, obtaining, or otherwise identifying or determining in any manner whatsoever using one or more of the devices shown in <FIG>.

Further, for simplicity of explanation, although the figures and descriptions herein may include sequences or series of steps or stages, elements of the methods disclosed herein can occur in various orders and/or concurrently. Additionally, elements of the methods disclosed herein may occur with other elements not explicitly presented and described herein. Furthermore, one or more elements of the methods described herein may be omitted from implementations of methods in accordance with the disclosed subject matter.

The implementations of the transmitting computing and communication device 100A and/or the receiving computing and communication device 100B (and the algorithms, methods, instructions, etc. stored thereon and/or executed thereby) can be realized in hardware, software, or any combination thereof. The hardware can include, for example, computers, intellectual property (IP) cores, application-specific integrated circuits (ASICs), programmable logic arrays, optical processors, programmable logic controllers, microcode, microcontrollers, servers, microprocessors, digital signal processors or any other suitable circuit. In the claims, the term "processor" should be understood as encompassing any of the foregoing hardware, either singly or in combination. The terms "signal" and "data" are used interchangeably. Further, portions of the transmitting computing and communication device 100A and the receiving computing and communication device 100B do not necessarily have to be implemented in the same manner.

Further, in one implementation, for example, the transmitting computing and communication device 100A or the receiving computing and communication device 100B can be implemented using a computer program that, when executed, carries out any of the respective methods, algorithms and/or instructions described herein. In addition, or alternatively, for example, a special purpose computer/processor can be utilized which can contain specialized hardware for carrying out any of the methods, algorithms, or instructions described herein.

The transmitting computing and communication device 100A and receiving computing and communication device 100B can, for example, be implemented on computers in a real-time video system. Alternatively, the transmitting computing and communication device 100A can be implemented on a server and the receiving computing and communication device 100B can be implemented on a device separate from the server, such as a hand-held communications device. In this instance, the transmitting computing and communication device 100A can encode content using an encoder <NUM> into an encoded video signal and transmit the encoded video signal to the communications device. In turn, the communications device can then decode the encoded video signal using a decoder <NUM>. Alternatively, the communications device can decode content stored locally on the communications device, for example, content that was not transmitted by the transmitting computing and communication device 100A. Other suitable transmitting computing and communication device 100A and receiving computing and communication device 100B implementation schemes are available. For example, the receiving computing and communication device 100B can be a generally stationary personal computer rather than a portable communications device and/or a device including an encoder <NUM> may also include a decoder <NUM>.

Further, all or a portion of implementations can take the form of a computer program product accessible from, for example, a tangible computer-usable or computer-readable medium. A computer-usable or computer-readable medium can be any device that can, for example, tangibly contain, store, communicate, or transport the program for use by or in connection with any processor. The medium can be, for example, an electronic, magnetic, optical, electromagnetic, or a semiconductor device. Other suitable mediums are also available.

It will be appreciated that aspects can be implemented in any convenient form. For example, aspects may be implemented by appropriate computer programs which may be carried on appropriate carrier media which may be tangible carrier media (e.g. disks) or intangible carrier media (e.g. communications signals). Aspects may also be implemented using suitable apparatus which may take the form of programmable computers running computer programs arranged to implement the methods and/or techniques disclosed herein. Aspects can be combined such that features described in the context of one aspect may be implemented in another aspect.

Claim 1:
A method for image decoding, comprising:
generating a reconstructed image, wherein generating the reconstructed image includes generating the reconstructed image using alpha channel prediction, wherein generating the reconstructed image using alpha channel prediction includes:
obtaining (<NUM>) reconstructed color channel values for a current pixel of the current image expressed with reference to a first color space;
obtaining (<NUM>) color space converted color channel values for the current pixel by converting the reconstructed color channel values to a second color space;
obtaining (<NUM>) an alpha channel lower bound for an alpha channel value for the current pixel using the color space converted color channel values;
generating (<NUM>) a candidate predicted alpha value for the current pixel;
obtaining (<NUM>) an adjusted predicted alpha value for the current pixel using the candidate predicted alpha value and the alpha channel lower bound;
obtaining a decoded residual alpha value and generating a reconstructed alpha value for the current pixel as a sum of the adjusted predicted alpha value and the decoded residual alpha value;
generating (<NUM>) a reconstructed pixel for the current pixel using the reconstructed alpha value; and
including the reconstructed pixel in the reconstructed image; and
outputting (<NUM>) the reconstructed image.