Patent Description:
The disclosure relates generally to the field of data processing, and more particularly to video encoding and/or decoding (e.g., by a coder, a decoder or a codec (decoder and encoder)).

AOMedia Video <NUM> (AV1) is an open video coding format designed for video transmissions over the Internet. It was developed as a successor to, for example, codec extensions in the related art.

<CIT> discloses techniques related to selecting constrained directional enhancement filters for video coding. Such techniques may include selecting subsets of constrained directional enhancement filters for use by a frame based on a frame level quantization parameter of the frame such that only the subset is used for filtering the frame.

Embodiments relate to a method, system, and computer readable medium for decoding video data. The scope of protection is defined by the claims annexed hereto.

These and other objects, features and advantages will become apparent from the following detailed description of illustrative embodiments, which is to be read in connection with the accompanying drawings. The various features of the drawings are not to scale as the illustrations are for clarity in facilitating the understanding of one skilled in the art in conjunction with the detailed description. In the drawings:.

In the description, details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the presented embodiments.

Embodiments relate generally to the field of data processing, and more particularly to video decoding. The following described exemplary embodiments provide a system, method and computer program to, among other things, decode video data.

As previously described, AOMedia Video <NUM> (AV1) is an open video coding format designed for video transmissions over the Internet. It was developed as a successor to VP9 by the Alliance for Open Media (AOMedia), a consortium founded in <NUM> that includes semiconductor firms, video on demand providers, video content producers, software development companies and web browser vendors.

Aspects are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer readable media according to the various embodiments.

Referring now to <FIG>, a functional block diagram of a networked computer environment illustrating a video coding system <NUM> (hereinafter "system") for encoding and/or decoding video data according to an embodiment. It should be appreciated that <FIG> provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements.

The system <NUM> may include a computer <NUM> and a server computer <NUM>. The computer <NUM> may communicate with the server computer <NUM> via a communication network <NUM> (hereinafter "network"). The computer <NUM> may include a processor <NUM> and a software program <NUM> that is stored on a data storage device <NUM> and is enabled to interface with a user and communicate with the server computer <NUM>. As will be discussed below with reference to <FIG> the computer <NUM> may include internal components 800A and external components 900A, respectively, and the server computer <NUM> may include internal components 800B and external components 900B, respectively. The computer <NUM> may be, for example, a mobile device, a telephone, a personal digital assistant, a netbook, a laptop computer, a tablet computer, a desktop computer, or any type of computing devices capable of running a program, accessing a network, and accessing a database.

The server computer <NUM> may also operate in a cloud computing service model, such as Software as a Service (SaaS), Platform as a Service (PaaS), or Infrastructure as a Service (laaS), as discussed below with respect to <FIG> and <FIG>. The server computer <NUM> may also be located in a cloud computing deployment model, such as a private cloud, community cloud, public cloud, or hybrid cloud.

The server computer <NUM>, which may be used for encoding video data is enabled to run a Video Encoding or Decoding Program <NUM> (hereinafter "program") that may interact with a database <NUM>. The Video Encoding or Decoding Program method is explained in more detail below with respect to <FIG>. In one embodiment, the computer <NUM> may operate as an input device including a user interface while the program <NUM> may run primarily on server computer <NUM>. In an alternative embodiment, the program <NUM> may run primarily on one or more computers <NUM> while the server computer <NUM> may be used for processing and storage of data used by the program <NUM>. It should be noted that the program <NUM> may be a standalone program or may be integrated into a larger video encoding program. The Video Encoding or Decoding Program <NUM> may be corresponding to an encoder, a decoder, or a coded (both encoder and decoder).

It should be noted, however, that processing for the program <NUM> may, in some instances be shared amongst the computers <NUM> and the server computers <NUM> in any ratio. In another embodiment, the program <NUM> may operate on more than one computer, server computer, or some combination of computers and server computers, for example, a plurality of computers <NUM> communicating across the network <NUM> with a single server computer <NUM>. In another embodiment, for example, the program <NUM> may operate on a plurality of server computers <NUM> communicating across the network <NUM> with a plurality of client computers. Alternatively, the program may operate on a network server communicating across the network with a server and a plurality of client computers.

The network <NUM> may include wired connections, wireless connections, fiber optic connections, or some combination thereof. In general, the network <NUM> can be any combination of connections and protocols that will support communications between the computer <NUM> and the server computer <NUM>. The network <NUM> may include various types of networks, such as, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, a telecommunication network such as the Public Switched Telephone Network (PSTN), a wireless network, a public switched network, a satellite network, a cellular network (e.g., a fifth generation (<NUM>) network, a long-term evolution (LTE) network, a third generation (<NUM>) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a metropolitan area network (MAN), a private network, an ad hoc network, an intranet, a fiber optic-based network, or the like, and/or a combination of these or other types of networks.

Additionally, or alternatively, a set of devices (e.g., one or more devices) of system <NUM> may perform one or more functions described as being performed by another set. of devices of system <NUM>.

In Versatile Video Coding (VVC) (Draft <NUM>), an Adaptive Loop Filter (ALF) with block-based filter adaption is applied. For the luma component, one among <NUM> filters is selected for each <NUM>×<NUM> block, based on the direction and activity of local gradients.

In VVC (Draft <NUM>), two diamond filter shapes (as shown in <FIG>) may be used. The <NUM>×<NUM> diamond shape is applied for luma component and the <NUM>×<NUM> diamond shape is applied for chroma components.

For luma component, each <NUM> × <NUM> block is categorized into one out of <NUM> classes. The classification index C is derived based on its directionality D and a quantized value of activity Â, as follows: <MAT>.

To calculate D and Â, gradients of the horizontal, vertical and two diagonal direction are first calculated using <NUM>-D Laplacian: <MAT> <MAT> <MAT> <MAT>.

Where indices i and j refer to the coordinates of the upper left sample within the <NUM> × <NUM> block and R(i, j) indicates a reconstructed sample at coordinate (i,j).

To reduce the complexity of block classification, the subsampled <NUM>-D Laplacian calculation is applied. As shown in <FIG>, the same subsampled positions are used for gradient calculation of all directions (e.g., a subsampled Laplacian calculation for all directions). For example, <FIG> shows subsampled positions for vertical gradient, <FIG> shows subsampled positions for horizontal gradient, and <FIG> and <FIG> show subsampled portions for diagonal gradients.

Then D maximum and minimum values of the gradients of horizontal and vertical directions are set as: <MAT>.

The maximum and minimum values of the gradient of two diagonal directions are set as: <MAT>.

To derive the value of the directionality D, these values are compared against each other and with two thresholds t<NUM> and t<NUM>:.

The activity value A is calculated as: <MAT>.

A is further quantized to the range of <NUM> to <NUM>, inclusively, and the quantized value is denoted as Â.

For chroma components in a picture, no classification method is applied, i.e. a single set of ALF coefficients is applied for each chroma component.

Before filtering each <NUM>×<NUM> luma block, geometric transformations such as rotation or diagonal and vertical flipping are applied to the filter coefficients f(k, l) and to the corresponding filter clipping values c(k, l) depending on gradient values calculated for that block. This is equivalent to applying these transformations to the samples in the filter support region. The idea is to make different blocks to which ALF is applied more similar by aligning their directionality.

Three geometric transformations, including diagonal, vertical flip and rotation are introduced: <MAT> <MAT> <MAT> where K is the size of the filter and <NUM> ≤ k, l ≤ K - <NUM> are coefficients coordinates, such that location (<NUM>,<NUM>) is at the upper left corner and location (K - <NUM>, K - <NUM>) is at the lower right corner. The transformations are applied to the filter coefficients f (k, l) and to the clipping values c(k, l) depending on gradient values calculated for that block. The relationship between the transformation and the four gradients of the four directions are summarized in the following Table <NUM>.

In VVC (Draft <NUM>), ALF filter parameters are signalled in adaptation parameter set (APS). In one APS, up to <NUM> sets of luma filter coefficients and clipping value indexes, and up to eight sets of chroma filter coefficients and clipping value indexes could be signalled. To reduce bits overhead, filter coefficients of different classification for luma component can be merged. In slice header, the indices of the APSs used for the current slice are signaled. The signaling of ALF is CTU-based in VVC (Draft <NUM>).

Clipping value indexes, which are decoded from the APS, allow determining clipping values using a table of clipping values for Luma and Chroma. These clipping values are dependent of the internal bitdepth. More precisely, the table of clipping values is obtained by the following formula: <MAT> with B equal to the internal bitdepth, α is a pre-defined constant value equal to <NUM>, and N equal to <NUM> which is the number of allowed clipping values in VVC (Draft <NUM>).

Table <NUM> shows the output of equation <NUM>.

In slice header, up to <NUM> APS indices can be signaled to specify the luma filter sets that are used for the current slice. The filtering process can be further controlled at coding tree block (CTB) level. A flag is always signalled to indicate whether ALF is applied to a luma CTB. A luma CTB can choose a filter set among <NUM> fixed filter sets and the filter sets from APSs. A filter set index is signaled for a luma CTB to indicate which filter set is applied. The <NUM> fixed filter sets are pre-defined and hardcoded in both the encoder and the decoder.

For chroma component, an APS index is signaled in slice header to indicate the chroma filter sets being used for the current slice. At CTB level, a filter index is signaled for each chroma CTB if there is more than one chroma filter set in the APS.

The filter coefficients may be quantized with norm equal to <NUM>. In order to restrict the multiplication complexity, a bitstream conformance is applied so that the coefficient value of the non-central position shall be in the range of -<NUM> to <NUM> - <NUM>, inclusive. The central position coefficient is not signalled in the bitstream and is considered as equal to <NUM>.

In VVC (Draft <NUM>), the syntaxes and semantics of clipping index and values are defined as follows: alf_luma_clip_idx[ sfIdx ][ j ] specifies the clipping index of the clipping value to use before multiplying by the j-th coefficient of the signalled luma filter indicated by sfIdx. It is a requirement of bitstream conformance that the values of alf_luma_clip_idx[ sfIdx ][ j ] with sfIdx = <NUM>. alf_luma_num_filters_signalled_minus1 and j = <NUM>. <NUM> shall be in the range of <NUM> to <NUM>, inclusive.

The luma filter clipping values AlfClipL[ adaptation_parameter_set_id ] with elements AlfClipL[ adaptation_parameter_set_id ][ filtIdx ][ j ], with
filtIdx = <NUM>. NumAlfFilters - <NUM> and j = <NUM>. <NUM> are derived as specified in Table <NUM> depending on bitDepth set equal to BitDepthY and clipIdx set equal to
alf_luma_clip_idx[ alf_luma_coeff_delta_idx[ filtIdx ] ][ j ].

alf_chroma_clip_idx[ altIdx ][ j ] specifies the clipping index of the clipping value to use before multiplying by the j-th coefficient of the alternative chroma filter with index altIdx. It is a requirement of bitstream conformance that the values of alf_chroma_clip_idx[ altIdx ][ j ] with altIdx = <NUM>. alf_chroma_num_alt_filters_minus1, j = <NUM>. <NUM> shall be in the range of <NUM> to <NUM>, inclusive.

The chroma filter clipping values AlfClipC[ adaptation_parameter_set_id ][ altIdx ] with elements AlfClipC[ adaptation_parameter_set_id ][ altIdx ][ j ], with
altIdx = <NUM>. alf_chroma_num_alt_filters_minus1, j = <NUM>. <NUM> are derived as specified in Table <NUM> depending on bitDepth set equal to BitDepthC and clipIdx set equal to
alf_chroma_clip_idx[ altIdx ][ j ].

At decoder side, when ALF is enabled for a CTB, each sample R(i, j) within the CU is filtered, resulting in sample value R'(i, j) as shown below, <MAT> where f(k, l) denotes the decoded filter coefficients, K(x, y) is the clipping function and c(k, l) denotes the decoded clipping parameters. The variable k and l vary between <MAT> and <MAT> where L denotes the filter length. The clipping function K(x, y) = min(y, max(-y, x)) which corresponds to the function Clip3 (-y, y, x). By incorporating this clipping function, this loop filtering method becomes a non-linear process, known as Non-Linear ALF. The selected clipping values are coded in the "alf_data" syntax element by using a Golomb encoding scheme corresponding to the index of the clipping value in Table <NUM>. This encoding scheme is the same as the encoding scheme for the filter index.

To reduce the line buffer requirement of ALF, modified block classification and filtering are employed for the samples near horizontal CTU boundaries. For this purpose, a virtual boundary may be defined as a line by shifting the horizontal CTU boundary with "N" samples as shown in <FIG>, with N equal to <NUM> for the Luma component and <NUM> for the Chroma component.

Modified block classification is applied for the Luma component as depicted in <FIG>. For the 1D Laplacian gradient calculation of the 4x4 block above the virtual boundary, only the samples above the virtual boundary are used. Similarly, for the 1D Laplacian gradient calculation of the 4x4 block below the virtual boundary, only the samples below the virtual boundary are used. The quantization of activity value A is accordingly scaled by taking into account the reduced number of samples used in 1D Laplacian gradient calculation.

For filtering processing, symmetric padding operation at the virtual boundaries are used for both Luma and Chroma components. As shown in <FIG> ("Modified ALF filtering for Luma component at virtual boundaries), when the sample being filtered is located below the virtual boundary, the neighboring samples that are located above the virtual boundary are padded. Meanwhile, the corresponding samples at the other sides are also padded, symmetrically.

In order enhance coding efficiency, the coding unit synchronous picture quadtree-based adaptive loop filter is proposed in JCTVC-C143 [<NUM>]. The luma picture is split into several multi-level quadtree partitions, and each partition boundary is aligned to the boundaries of the largest coding units (LCUs). Each partition has its own filtering process and thus be called as a filter unit (FU).

The <NUM>-pass encoding flow is described as follows. At the first pass, the quadtree split pattern and the best filter of each FU are decided. The filtering distortions are estimated by FFDE during the decision process. According to the decided quadtree split pattern and the selected filters of all FUs, the reconstructed picture is filtered. At the second pass, the CU synchronous ALF on/off control is performed. According to the ALF on/off results, the first filtered picture is partially recovered by the reconstructed picture.

A top-down splitting strategy is adopted to divide a picture into multi-level quadtree partitions by using a rate-distortion criterion. Each partition is called a filter unit. The splitting process aligns quadtree partitions with LCU boundaries. The encoding order of FUs follows the z-scan order. For example, the picture may be split into <NUM> FUs, and the encoding order is FU0, FU1, FU2, FU3, FU4, FU5, FU6, FU7, FU8, and FU9.

To indicate the picture quadtree split pattern, split flags may be encoded and transmitted in z-order.

The filter of each FU may be selected from two filter sets based on the rate-distortion criterion. The first set may have <NUM>/<NUM>-symmetric square-shaped and rhombus-shaped filters newly derived for the current FU. The second set may come from time-delayed filter buffers; the time-delayed filter buffers store the filters previously derived for FUs of prior pictures. The filter with the minimum rate-distortion cost of these two sets may be chosen for the current FU. Similarly, if the current FU is not the smallest FU and can be further split into <NUM> children FUs, the rate-distortion costs of the <NUM> children FUs are calculated. By comparing the rate-distortion cost of the split and non-split cases recursively, the picture quadtree split pattern can be decided.

The maximum quadtree split level is <NUM> in JCTVC-C143, which means the maximum number of FUs is <NUM>. During the quadtree split decision, the correlation values for deriving Wiener coefficients of the <NUM> FUs at the bottom quadtree level (smallest FUs) can be reused. The rest FUs can derive their Wiener filters from the correlations of the 16FUs at the bottom quadtree level. Therefore, there is only one frame buffer access for deriving the filter coefficients of all FUs.

After the quadtree split pattern is decided, to further reduce the filtering distortion, the CU synchronous ALF on/off control is performed. By comparing the filtering distortion and non-filtering distortion, the leaf CU can explicitly switch ALF on/off in its local region. The coding efficiency may be further improved by redesigning the filter coefficients according to the ALF on/off results. However, the redesigning process needs additional frame buffer accesses. In the proposed CS-PQALF encoder design, there is no redesign process after the CU synchronous ALF on/off decision in order to minimize the number of frame buffer accesses.

Cross-component adaptive loop filter (CC-ALF) makes use of luma sample values to refine each chroma component.

CC-ALF operates by applying a linear, diamond shaped filter to the luma channel for each chroma component. The filter coefficients are transmitted in the APS, scaled by a factor of <NUM><NUM>, and rounded for fixed point representation. The application of the filters is controlled on a variable block size and signalled by a context-coded flag received for each block of samples. The block size along with an CC-ALF enabling flag is received at the slice-level for each chroma component. In the contribution the following block sizes (in chroma samples) were supported 16x16, 32x32, 64x64.

Syntax changes of CC-ALF are described below in Table <NUM>.

The semantics of CC-ALF related syntaxes are described below:.

<FIG> ("Location of chroma samples relative to luma samples") of the present application illustrates the indicated relative position of the top-left chroma sample when chroma_format_idc is equal to <NUM> (<NUM>:<NUM>:<NUM> chroma format), and chroma _sample_loc_type_top_field or chroma_sample_loc_type_bottom_field is equal to the value of a variable ChromaLocType. The region represented by the top-left <NUM>:<NUM>:<NUM> chroma sample (depicted as a large red square with a large red dot at its centre) is shown relative to the region represented by the top-left luma sample (depicted as a small black square with a small black dot at its centre). The regions represented by neighbouring luma samples are depicted as small grey squares with small grey dots at their centres.

The main goal of the in-loop constrained directional enhancement filter (CDEF) is to filter out coding artifacts while retaining the details of the image. In HEVC, the Sample Adaptive Offset (SAO) algorithm achieves a similar goal by defining signal offsets for different classes of pixels. Unlike SAO, CDEF is a non-linear spatial filter. The design of the filter has been constrained to be easily vectorizable (i.e. implementable with SIMD operations), which was not the case for other non-linear filters like the median filter and the bilateral filter.

The CDEF design originates from the following observations. The amount of ringing artifacts in a coded image tends to be roughly proportional to the quantization step size. The amount of detail is a property of an input image, but the smallest detail retained in the quantized image tends to also be proportional to the quantization step size. For a given quantization step size, the amplitude of the ringing is generally less than the amplitude of the details.

CDEF works by identifying the direction of each block and then adaptively filtering along the identified direction and to a lesser degree along directions rotated <NUM> degrees from the identified direction. The filter strengths are signaled explicitly, which allows a high degree of control over the blurring. An efficient encoder search is designed for the filter strengths. CDEF is based on two previously proposed in-loop filters and the combined filter was adopted for the emerging AV1 codec.

The direction search operates on the reconstructed pixels, just after the deblocking filter. Since those pixels are available to the decoder, the directions require no signaling. The search operates on <NUM> × <NUM> blocks, which are small enough to adequately handle non-straight edges, while being large enough to reliably estimate directions when applied to a quantized image. Having a constant direction over an <NUM>×<NUM> region also makes vectorization of the filter easier. For each block we determine the direction that best matches the pattern in the block by minimizing the sum of squared differences (SSD) between the quantized block and the closest perfectly directional block. A perfectly directional block is a block where all of the pixels along a line in one direction have the same value. <FIG> is an example of direction search for an <NUM> × <NUM> block. In this case, the <NUM>-degree direction (as shown by the box around column <NUM>) is selected because it minimizes the error.

The main reason for identifying the direction is to align the filter taps along that direction to reduce ringing while preserving the directional edges or patterns. However, directional filtering alone sometimes cannot sufficiently reduce ringing. It is also desired to use filter taps on pixels that do not lie along the main direction. To reduce the risk of blurring, these extra taps are treated more conservatively. For this reason, CDEF defines primary taps and secondary taps. The complete <NUM>-D CDEF filter is expressed as <MAT> where D is the damping parameter, S(p) and S(s) are the strengths of the primary and secondary taps, respectively, and round(·) rounds ties away from zero, wk are the filter weights and f(d, S, D) is a constraint function operating on the difference between the filtered pixel and each of the neighboring pixels. For small differences, f(d, S, D) = d, making the filter behave like a linear filter. When the difference is large, f(d, S, D) = <NUM>, which effectively ignores the filter tap.

A set of in-loop restoration schemes are proposed for use in video coding post deblocking, to generally denoise and enhance the quality of edges, beyond the traditional deblocking operation. These schemes are switchable within a frame per suitably sized tile. The specific schemes described are based on separable symmetric Wiener filters and dual self-guided filters with subspace projection. Because content statistics can vary substantially within a frame, these tools are integrated within a switchable framework where different tools can be triggered in different regions of the frame.

One restoration tool that has been shown to be promising in the literature is the Wiener filter. Every pixel in a degraded frame could be reconstructed as a non-causal filtered version of the pixels within a w × w window around it where w = 2r + <NUM> is odd for integer r. If the 2D filter taps are denoted by a w<NUM> × <NUM> element vector F in column-vectorized form, a straightforward LMMSE optimization leads to filter parameters being given by F = H-<NUM> M, where H = E[XXT] is the autocovariance of x, the column-vectorized version of the w<NUM> samples in the w × w window around a pixel, and M = E[YXT] is the cross correlation of x with the scalar source sample y, to be estimated. The encoder can estimate H and M from realizations in the deblocked frame and the source and send the resultant filter F to the decoder. However, that would not only incur a substantial bit rate cost in transmitting w<NUM> taps, but also non-separable filtering will make decoding prohibitively complex. Therefore, several additional constraints are imposed on the nature of F. First, F is constrained to be separable so that the filtering can be implemented as separable horizontal and vertical w-tap convolutions. Second, each of the horizontal and vertical filters are constrained to be symmetric. Third, the sum of both the horizontal and vertical filter coefficients is assumed to sum to <NUM>.

Guided filtering is one of the more recent paradigms of image filtering where a local linear model: <MAT> is used to compute the filtered output y from an unfiltered sample x, where F and G are determined based on the statistics of the degraded image and a guidance image in the neighborhood of the filtered pixel. If the guide image is the same as the degraded image, the resultant so-called self-guided filtering has the effect of edge preserving smoothing. The specific form of self-guided filtering we propose depends on two parameters: a radius r and a noise parameter e, and is enumerated as follows:.

Filtering is controlled by r and e, where a higher r implies a higher spatial variance and a higher e implies a higher range variance.

The principle of subspace projection is illustrated diagrammatically in <FIG>. Even though none of the cheap restorations X<NUM>, X<NUM> are close to the source Y, appropriate multipliers {α, β} can bring them much closer to the source as long as they are moving somewhat in the right direction. <FIG> shows a subspace projection using cheap restorations to produce a final restoration closer to the source.

A semi decoupled partitioning (SDP) scheme, or a semi separate tree (SST) or flexible block partitioning for chroma component. In this method, luma and chroma block in one super block (SB) may have same or different block partitioning, which is dependent on the luma coded block sizes or the luma tree depth. To be specific, when the luma block area size is greater than one threshold T1 or coding tree splitting depth of luma block is smaller than or equal to one threshold T2, then chroma block uses the same coding tree structure as luma. Otherwise when the block area size is smaller than or equal to T1 or luma splitting depth is larger than T2, the corresponding chroma block can have different coding block partitioning with luma component, which is called flexible block partitioning for chroma component. T1 is a positive integer, such as <NUM> or <NUM>. T2 is a positive integer, such as <NUM> or <NUM>.

An improved semi decoupled partitioning (SDP) scheme was proposed, wherein luma and chroma component may share the partial tree structure from the root node of the super block, and the condition on when luma and chroma start separate tree partitioning depends on partitioning information of luma. For example, <FIG> shows an example of the coding tree structure for luma and chroma component.

In Constrained Directional Enhancement Filter (CDEF), luma and chroma components are limited to share presets at picture level. Additionally, luma and chroma components are also limited to have the same preset index at block level. Lastly, when deriving the filter strength of chroma component, luma block size is used to determine an input of chroma component. These constraints may limit the coding efficiency of CDEF.

In traditional CDEF, one preset contains luma and chroma primary/secondary strength. The number of allowed/available presets are signaled at picture level. At coded block level, an index is signaled to indicate which preset is selected for current block. Coded block sizes of CDEF include128x128, 128x64, 64x64, and 64x128. There are three limitations of traditional CDEF: one limitation is that luma and chroma components are forced to share presets at picture level; another limitation is that luma and chroma components are forced to pick the same preset index at block level; one more limitation is that when deriving the filter strength of chroma component, luma block size is used to determine an input of chroma component. The aforementioned limitations together may limit the performance of CDEF, especially under the situation when luma and chroma components have different partitioning scheme, such as the partitioning scheme in semi decoupled partitioning (SDP).

In this document, a Separate Constrained Directional Enhancement Filter (SCDEF) is proposed which performs the CDEF process of luma and chroma components separately. Compared with traditional CDEF, SCDEF allows the filtering of luma and chroma components independent from each other. To be more specific, luma and chroma components may have different number of presets at picture level; Moreover, luma and chroma components may select different preset index at block level; When deriving the filter strength of chroma component, chroma block size is used to determine an input of chroma component.

It is proposed that when luma and chroma components have different partitioning or semi-decoupled partitioning, CDEF filtering process of luma and chroma components are performed separately, as shown in <FIG>. An input of the CDEF filtering process is the reconstructed samples of luma/chroma components. The intermediate output of this process includes but not limited to the derived filter presets and per-block level preset index as mentioned in the above proposed method. The eventual output of this process is the filtered reconstructed samples of luma/chroma components.

In one embodiment, the number of presets derived for luma and chroma component may be different from each other at picture level. An input of the CDEF filtering process is the reconstructed samples in luma/chroma component. The output of this process is the derived presets at picture level. Example number of presets at picture level include but not limited to <NUM>, <NUM>, <NUM>, <NUM>.

In one example, the number of presets derived and selected for current luma component in one frame is <NUM>, and the number of presets derived and selected for current chroma component in this frame is <NUM>.

In another example, the number of presets derived and selected for luma component is N, N is a positive integer, such as <NUM>, <NUM>, <NUM>, or <NUM>, whereas the number of presets for chroma component is fixed as <NUM>. The number of presets for chroma component does not need to be signaled in the bitstream, and derived as <NUM> in the decoder.

For example, <FIG> shows a Separate Constrained Directional Enhancement Filter (SCDEF).

In one embodiment, the selected preset index for current luma and chroma block may be different from each other. An input of this process is luma/chroma reconstructed samples of current block, and the presets derived and selected at frame level. The output of this process is an index indicating which preset is selected for current block.

In one example, when luma component has <NUM> presets and chroma component has <NUM> presets at frame level, the preset index selected for luma block A is <NUM>, and the preset index selected for chroma block B is <NUM>. Luma block A and chroma block B are co-located or partially co-located.

In one embodiment, when deriving the CDEF filtering strength of chroma component, an input reconstructed sample is determined by current chroma coded block size.

In one example, when current chroma block is of size 32x64, an input is chroma reconstructed sample values of current 32x64 block.

In one unclaimed embodiment, when separate partitioning or semi de-coupled partitioning is applied to luma and chroma blocks, luma and chroma blocks still share the same preset index, and only the luma (or chroma) block size is employed in the preset index derivation/signaling process.

In some embodiments, when luma and chroma components have the same coded block size, the CDEF filtering process of luma and chroma components are performed separately.

In some embodiments, the signaling of SCDEF are performed separately for luma and chroma components.

In one embodiment, picture level presets are signaled separately for luma and chroma components. These presets can be signaled in high-level parameter set (DPS, VPS, SPS, PPS, APS), slice header, picture header, SEI message.

In one example, luma presets are signaled first, then, chroma presets are signaled.

In one embodiment, block level preset indexes are signaled separately for luma and chroma components.

In one example, preset indexes of luma component are signaled first, then, preset indexes of chroma component are signaled.

Referring now to <FIG>, an operational flowchart illustrating the steps of a method <NUM> for decoding video data is depicted. However, one of ordinary skill can appreciate how the encoding process would work based on <FIG>. In some implementations, one or more process blocks of <FIG> may be performed by the computer <NUM> (<FIG>) and the server computer <NUM> (<FIG>). In some implementations, one or more process blocks of <FIG> may be performed by another device or a group of devices separate from or including the computer <NUM> and the server computer <NUM>.

At <NUM>, the method <NUM> includes receiving video data comprising a chroma component and a luma component.

At <NUM>, the method <NUM> includes parsing, deriving or selecting a number of presets for the chroma component in one frame, and a number of presets for the luma component in the one frame.

At <NUM>, the method <NUM> includes encoding and/or decoding the video data.

Operation <NUM> may be based on the number of presets for the chroma component in one frame, and the number of presets for the luma component in the one frame.

The method may further comprise: performing a separate Constrained Directional Enhancement Filter (CDEF) process of filtering luma and chroma components independent from each other based on the number of presets for the chroma component in one frame, and the number of presets for the luma component in the one frame.

It may be appreciated that <FIG> provides only an illustration of one implementation and does not imply any limitations with regard to how different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements.

<FIG> is a block diagram <NUM> of internal and external components of computers depicted in <FIG> in accordance with an illustrative embodiment. It should be appreciated that <FIG> provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements.

Computer <NUM> (<FIG>) and server computer <NUM> (<FIG>) may include respective sets of internal components 800A,B and external components 900A,B illustrated in <FIG>. Each of the sets of internal components <NUM> include one or more processors <NUM>, one or more computer-readable RAMs <NUM> and one or more computer-readable ROMs <NUM> on one or more buses <NUM>, one or more operating systems <NUM>, and one or more computer-readable tangible storage devices <NUM>.

Processor <NUM> is implemented in hardware, firmware, or a combination of hardware and software. Processor <NUM> is a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or another type of processing component. In some implementations, processor <NUM> includes one or more processors capable of being programmed to perform a function. Bus <NUM> includes a component that permits communication among the internal components 800A,B.

The one or more operating systems <NUM>, the software program <NUM> (<FIG>) and the Video Encoding Program <NUM> (<FIG>) on server computer <NUM> (<FIG>) are stored on one or more of the respective computer-readable tangible storage devices <NUM> for execution by one or more of the respective processors <NUM> via one or more of the respective RAMs <NUM> (which typically include cache memory). In the embodiment illustrated in <FIG>, each of the computer-readable tangible storage devices <NUM> is a magnetic disk storage device of an internal hard drive. Alternatively, each of the computer-readable tangible storage devices <NUM> is a semiconductor storage device such as ROM <NUM>, EPROM, flash memory, an optical disk, a magneto-optic disk, a solid state disk, a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and/or another type of non-transitory computer-readable tangible storage device that can store a computer program and digital information.

Each set of internal components 800A,B also includes a R/W drive or interface <NUM> to read from and write to one or more portable computer-readable tangible storage devices <NUM> such as a CD-ROM, DVD, memory stick, magnetic tape, magnetic disk, optical disk or semiconductor storage device. A software program, such as the software program <NUM> (<FIG>) and the Video Encoding Program <NUM> (<FIG>) can be stored on one or more of the respective portable computer-readable tangible storage devices <NUM>, read via the respective R/W drive or interface <NUM> and loaded into the respective hard drive <NUM>.

Each set of internal components 800A,B also includes network adapters or interfaces <NUM> such as a TCP/IP adapter cards; wireless Wi-Fi interface cards; or <NUM>, <NUM>, or <NUM> wireless interface cards or other wired or wireless communication links. The software program <NUM> (<FIG>) and the Video Encoding Program <NUM> (<FIG>) on the server computer <NUM> (<FIG>) can be downloaded to the computer <NUM> (<FIG>) and server computer <NUM> from an external computer via a network (for example, the Internet, a local area network or other, wide area network) and respective network adapters or interfaces <NUM>. From the network adapters or interfaces <NUM>, the software program <NUM> and the Video Encoding Program <NUM> on the server computer <NUM> are loaded into the respective hard drive <NUM>. The network may comprise copper wires, optical fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers.

Each of the sets of external components 900A,B can include a computer display monitor <NUM>, a keyboard <NUM>, and a computer mouse <NUM>. External components 900A,B can also include touch screens, virtual keyboards, touch pads, pointing devices, and other human interface devices. Each of the sets of internal components 800A,B also includes device drivers <NUM> to interface to computer display monitor <NUM>, keyboard <NUM> and computer mouse <NUM>. The device drivers <NUM>, R/W drive or interface <NUM> and network adapter or interface <NUM> comprise hardware and software (stored in storage device <NUM> and/or ROM <NUM>).

It is understood in advance that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, some embodiments are capable of being implemented in conjunction with any other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service.

Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service.

Infrastructure as a Service (laaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).

Deployment Models are as follows:
Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.

Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load- balancing between clouds).

At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes.

Referring to <FIG>, illustrative cloud computing environment <NUM> is depicted. As shown, cloud computing environment <NUM> comprises one or more cloud computing nodes <NUM> with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone 54A, desktop computer 54B, laptop computer 54C, and/or automobile computer system 54N may communicate. Cloud computing nodes <NUM> may communicate with one another. It is understood that the types of computing devices 54A-N shown in <FIG> are intended to be illustrative only and that cloud computing nodes <NUM> and cloud computing environment <NUM> can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).

Referring to <FIG>, a set of functional abstraction layers <NUM> provided by cloud computing environment <NUM> (<FIG>) is shown. It should be understood in advance that the components, layers, and functions shown in <FIG> are intended to be illustrative only and embodiments are not limited thereto.

In one example, these resources may comprise application software licenses.

Workloads layer <NUM> provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation <NUM>; software development and lifecycle management <NUM>; virtual classroom education delivery <NUM>; data analytics processing <NUM>; transaction processing <NUM>; and Video Encoding/Decoding <NUM>.

Some embodiments may relate to a system, a method, and/or a computer readable medium at any possible technical detail level of integration. The computer readable medium may include a computer-readable non-transitory storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out operations.

Computer readable program code/instructions for carrying out operations may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the "C" programming language or similar programming languages. In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects or operations.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer readable media according to various embodiments. The method, computer system, and computer readable medium may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in the Figures. For example, two blocks shown in succession may, in fact, be executed concurrently or substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.

No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles "a" and "an" are intended to include one or more items, and may be used interchangeably with "one or more. " Furthermore, as used herein, the term "set" is intended to include one or more items (e.g., related items, unrelated items, a combination of related and unrelated items, etc.), and may be used interchangeably with "one or more. " Where only one item is intended, the term "one" or similar language is used. Also, as used herein, the terms "has," "have," "having," or the like are intended to be open-ended terms. Further, the phrase "based on" is intended to mean "based, at least in part, on" unless explicitly stated otherwise.

The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claim 1:
A method of video decoding, executable by a processor, the method comprising:
receiving video data comprising a chroma component and a luma component, wherein the luma and chroma components share the partition tree structure from the root node of a super block, and the condition on when luma and chroma components start separate tree partitioning depends on partitioning information of said luma component;
parsing, deriving or selecting a number of presets for the chroma component in one frame, and a number of presets for the luma component in the one frame; and
decoding the video data, wherein the method comprises, when the luma and chroma components have different partitioning or semi-decoupled partitioning, performing a separate Constrained Directional Enhancement Filter CDEF process of filtering luma and chroma components independent from each other based on the number of presets for the chroma component in one frame, and the number of presets for the luma component in the one frame, wherein the number of presets derived for the luma component is different from the number of presets derived for the chroma component at picture level, wherein block level preset indexes indicating a selected preset are signaled separately for luma and chroma components.