Video coding and decoding using cross-component linear model

Abstract

A method and computing device are provided for video coding and decoding. The method may include deriving a parameter alpha and a parameter beta for the CCLM mode by using a predetermined number of neighboring reconstructed luma samples and chroma samples in the CU; and generating a final chroma prediction value for the chroma sample of the CU by using the parameter alpha and the parameter beta.

Description

[0001] This application is a divisional application of the same patent application, filed on January 8, 2020, with application number 202080008587.4. Cross-reference to related applications

[0002] This application claims the benefit of U.S. Provisional Application No. 62 / 790,459, filed January 9, 2019. The entire disclosure of the above application is incorporated herein by reference. Technical Field

[0003] This disclosure generally relates to video encoding / decoding and compression. More specifically, this disclosure relates to systems and methods for performing video encoding / decoding using a cross-component linear model. In particular example embodiments, a method for obtaining final chroma prediction values ​​for chroma samples used in the encoding / decoding unit is described. Background Technology

[0004] This section provides background information relating to this disclosure. The information contained in this section is not necessarily to be construed as prior art.

[0005] Various video codec techniques can be used to compress video data. Video codecs are performed according to one or more video codec standards. Examples of video codec standards include Universal Video Codec (VVC), Joint Explore Test Model (JEM), High Efficiency Video Codec (H.265 / HEVC), High-Level Video Codec (H.264 / AVC), and Moving Picture Experts Group (MPEG) codecs. Video codecs typically use prediction methods that utilize redundancy present in video images or sequences (e.g., inter-frame prediction, intra-frame prediction, etc.). A key goal of video codec techniques is to compress video data into a form using a lower bitrate while avoiding or minimizing video quality degradation. As evolving video services become available, there is a need for codec techniques with better compression efficiency. Summary of the Invention

[0006] This section provides a general overview of the contents of this disclosure, but is not a full disclosure of its entire scope or all its features.

[0007] According to a first aspect of this disclosure, a video encoding / decoding method is executed at a computing device having one or more processors and a memory storing multiple programs to be executed by the one or more processors. The method includes deriving a first parameter α and a second parameter β for a cross-component linear model (CCLM) mode using a predetermined number of adjacent reconstructed luminance and chrominance samples in an encoding / decoding unit (CU); and generating a final chrominance prediction value for the chrominance samples of the CU using the first parameter α and the second parameter β.

[0008] According to a second aspect of this disclosure, a computing device is provided. The computing device includes at least one processor; a non-transitory storage device coupled to one or more processors; and a plurality of programs stored in the non-transitory storage device, which, when executed by the processor, cause the computing device to perform actions including: deriving a first parameter α and a second parameter β for a Cross Component Linear Model (CCLM) mode using a predetermined number of adjacent reconstructed luminance and chrominance samples in a codec unit (CU); and generating a final chrominance prediction value for the chrominance samples of the CU using the first parameter α and the second parameter β. Attached Figure Description

[0009] In the following description, a set of illustrative, non-limiting embodiments of the present disclosure will be described in conjunction with the accompanying drawings. Those skilled in the art can implement variations of the structures, methods, or functions based on the examples given herein, and all such variations are included within the scope of this disclosure. Where there is no conflict, the teachings of different embodiments can, but do not necessarily, be combined with each other.

[0010] Figure 1 It is a block diagram illustrating an illustrative encoder that can be used in conjunction with many video codec standards.

[0011] Figure 2 It is a block diagram illustrating a decoder that can be used in conjunction with many video codec standards.

[0012] Figure 3 This is a flowchart of video encoding and decoding methods.

[0013] Figure 4 This is an example of a luminance / chrominance pixel sampling grid.

[0014] Figure 5 The locations of the samples used to derive α and β are shown.

[0015] Figure 6 The linear derivation of α and β using the min-max method is shown.

[0016] Figure 7 The LM_A mode is shown.

[0017] Figure 8 The LM_L mode is shown.

[0018] Figure 9 It is a luminance / chrominance pixel sampling grid for YUV 4:2:2 format.

[0019] Figure 10 It is a luminance / chrominance pixel sampling grid for YUV 4:4:4 format.

[0020] Figure 11 Multiple neighbors are shown for MMLM.

[0021] Figure 12 The locations of three sample pairs are shown as examples.

[0022] Figure 13 The location of another example of three sample pairs is shown.

[0023] Figure 14 The locations of four sample pairs are shown.

[0024] Figure 15 The location of another example of four sample pairs is shown. Detailed Implementation

[0025] The terminology used in this disclosure is intended to illustrate specific examples and not to limit the disclosure. The singular forms “a,” “an,” and “the” used in this disclosure and the appended claims also refer to the plural forms unless the context explicitly includes otherwise. It should be understood that the term “and / or” as used herein refers to any or all possible combinations of one or more of the associated listed items.

[0026] It should be understood that while the terms “first,” “second,” “third,” etc., may be used herein to describe various types of information, such information should not be limited by these terms. These terms are used only to distinguish one type of information from another. For example, without departing from the scope of this disclosure, first information may be referred to as second information; and similarly, second information may be referred to as first information. As used herein, depending on the context, the term “if” may be understood to mean “when,” “once,” or “in response to.”

[0027] Throughout this specification, references to "an embodiment," "one embodiment," "another embodiment," etc., in the singular or plural form, mean that one or more specific features, structures, or characteristics described in connection with the embodiment are included in at least one embodiment of this disclosure. Therefore, phrases such as "in one embodiment," "in one way," "in another way," etc., appearing in the singular or plural form throughout the specification do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable manner.

[0028] Conceptually, many video codec standards are similar, including those mentioned earlier in the background section. For example, almost all video codec standards use block-based processing and share similar video codec diagrams for video compression.

[0029] Figure 1 A block diagram of an illustrative encoder 100 that can be used in conjunction with many video codec standards is shown. In encoder 100, video frames are divided into multiple video blocks for processing. For each given video block, a prediction is formed based on either an inter-frame prediction method or an intra-frame prediction method. In inter-frame prediction, one or more prediction values ​​are formed based on pixels from previously reconstructed frames through motion estimation and motion compensation. In intra-frame prediction, prediction values ​​are formed based on reconstructed pixels in the current frame. Through mode decision, the best prediction value can be selected to predict the current block.

[0030] The prediction residual, representing the difference between the current video block and its predicted value, is sent to the transform circuit 102. The transform coefficients are then sent from the transform circuit 102 to the quantization circuit 104 for entropy reduction. The quantization coefficients are then fed to the entropy encoding / decoding circuit 106 to generate a compressed video bitstream. Figure 1 As shown, prediction-related information 110 (such as video block partitioning information, motion vectors, reference picture indexes, and intra-prediction modes) from the inter-frame prediction circuit and / or intra-frame prediction circuit 112 is also fed through the entropy encoding / decoding circuit 106 and stored in the compressed video bitstream 114.

[0031] In encoder 100, additional circuitry associated with the decoder is required to reconstruct pixels for prediction purposes. First, the prediction residual is reconstructed via inverse quantization 116 and inverse transform circuitry 118. This reconstructed prediction residual is combined with block prediction values ​​120 to generate unfiltered reconstructed pixels for the current video block.

[0032] To improve encoding / decoding efficiency and visual quality, loop filters are commonly used. For example, deblocking filters are available in current versions of AVC, HEVC, and VVC. In HEVC, an additional loop filter called SAO (Sample Adaptive Offset) is defined to further improve encoding / decoding efficiency. In the current version of the VVC standard, another loop filter called ALF (Adaptive Loop Filter) is under active research and is very likely to be included in the final standard.

[0033] These loop filter operations are optional. Performing these operations helps improve encoding / decoding efficiency and visual quality. They can also be turned off as a decision made by encoder 100 to save computational complexity.

[0034] It should be noted that intra-frame prediction is typically based on unfiltered reconstructed pixels, while inter-frame prediction is based on filtered reconstructed pixels if these filter options are enabled by encoder 100.

[0035] Figure 2This is a block diagram illustrating a decoder 200 that can be used in conjunction with many video codec standards. This decoder 200 is similar to one residing in... Figure 1 The reconstruction-related part in encoder 100. In decoder 200 ( Figure 2 In the process, the incoming video bitstream is first decoded by entropy decoding 202 to derive quantization coefficient levels and prediction-related information. Then, the quantization coefficient levels are processed by inverse quantization 204 and inverse transform 206 to obtain the reconstructed prediction residual. The block prediction mechanism implemented in the intra / inter-frame mode selector 212 is configured to perform either intra-frame prediction 208 or motion compensation 210 based on the decoded prediction information. The set of unfiltered reconstructed pixels is obtained by adding the reconstructed prediction residual from inverse transform 206 to the prediction output generated by the block prediction mechanism using adder 214. With the loop filter enabled, filtering is performed on these reconstructed pixels to derive the final reconstructed video for output.

[0036] To reduce cross-component redundancy, VVC uses a Cross-Component Linear Model (CCLM) prediction mode. During VVC development, the YUV format 4:2:0 was used under common test conditions, and... Figure 4 The image shows the sampling grid for luma and chroma samples in YUV format 4:2:0. The coordinates of the luma and chroma samples (downsampled luma samples) are also shown. Figure 4 As shown in the figure, RecL'[x, y] represents the top and left adjacent reconstructed luminance samples after downsampling, and RecC'[x,y] represents the top and left adjacent reconstructed chrominance samples, where x and y are pixel indices. In this disclosure, we propose several methods to reduce the complexity of CCLM parameter derivation.

[0037] This disclosure generally relates to encoding and decoding (e.g., encoding and decoding) video data. More specifically, this disclosure relates to a video encoding and decoding method and computing device for reducing cross-component redundancy in video encoding and decoding methods. A CCLM prediction model is used to predict chroma samples based on reconstructed luminance samples from the same CU for the CCLM prediction model. A computing device includes: at least one processor; a non-transitory storage device coupled to one or more processors; and a plurality of programs stored in the non-transitory storage device, which, when executed by the processor, cause the computing device to perform actions of a video encoding and decoding method.

[0038] like Figure 3 As shown, a video encoding / decoding method includes at least the following steps:

[0039] Step 10: Derive the first parameter α and the second parameter β for the CCLM mode by using a predetermined number of adjacent reconstructed luminance and chrominance samples in the CU.

[0040] Step 20: Generate the final chromaticity prediction value for the CU chromaticity sample by using the first parameter α and the second parameter β.

[0041] In step 20, the final chromaticity prediction values ​​for the chromaticity samples of the CU are generated using the following equation:

[0042] (1)

[0043] in These are the final chromaticity prediction values ​​for the chromaticity samples of CU. It is the reconstructed brightness sample of the CU downsampled, where x represents the row index and y represents the column index.

[0044] The coordinates of the luminance sample and the chrominance sample (downsampled luminance sample) are in Figure 5 As shown in the image.

[0045] The parameters α and β are derived from the following equation (referred to as the mini-maximum method in the following sections):

[0046] (2)

[0047] Each chromaticity sample and its corresponding luminance sample are called a sample pair. Where y B y represents the chromaticity sample value of the largest sample pair. A x is the chromaticity sample value of the smallest sample pair. B x represents the brightness sample value of the largest sample pair. A The brightness sample value is the smallest sample pair.

[0048] like Figure 6 The two points (a pair of luminance and chromaticity) (A, B) depicted are the minimum and maximum values ​​within the set of adjacent luminance samples. Figure 6 It is a graph of the straight line between the minimum brightness value and the maximum brightness value, where the linear model parameters α and β are obtained according to equation (2).

[0049] exist Figure 5 In the middle, Rec L [x, y] represents the top and left adjacent reconstructed brightness samples after downsampling, Rec C [x, y] represents the top and left adjacent reconstructed chroma samples, where x represents the row index and y represents the column index. Note that... Figure 5 The square blocks in the image are reconstructed brightness samples, and these reconstructed brightness samples correspond to... Figure 4 The location of the brightness sample depicted in the image; Figure 5 The circles in the middle correspond to Figure 4The location of the chroma sample or downsampled luminance sample depicted in the code. For square codec blocks, the min-max method is applied directly. For non-square codec blocks, adjacent samples of the longer boundary are first subsampled to have the same number of samples as the shorter boundary. Figure 5 This shows the positions of the left and top samples and the current block sample involved in the CCLM mode.

[0050] The min-max method computation is performed as part of the decoding process, not just as an encoder search operation. Therefore, the values ​​of parameters α and β are not transmitted to the decoder using syntax. Currently, equation / filter (3) is used as a luminance downsampling filter to generate downsampled luminance samples. However, as shown in equations (3) to (19), different equations / filters can be selected to generate downsampled luminance samples. Note that equations (5) to (10) can be considered as directly obtaining samples without a downsampling process. (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16)

[0051] Besides the top and left templates, which can be used together to calculate linear model coefficients, they can also be used alternatively in two other LM modes, referred to as the LM_A mode and the LM_L mode, respectively. For example... Figure 7 As shown, in LM_A mode, the upper template is used to calculate the coefficients of the linear model. To obtain more samples, the upper template is extended to (W+H). Figure 8As shown, in LM_L mode, only the left template is used to calculate the linear model coefficients. To obtain more samples, the left template is expanded to (H+W). For non-square blocks, the top template is expanded to W+W, and the left template is expanded to H+H. When the top / left template is unavailable, the LM_A / LM_L mode will not be checked or signaled. When there are insufficient available samples, the template is padded by copying the rightmost (for the top template) sample or the bottommost (for the left template) sample to the nearest log2 number. In addition to the 4:2:0 YUV format, the codec can also support the 4:2:2 format (e.g., Figure 9 (as shown) and 4:4:4 format (as shown) Figure 10 (As shown).

[0052] As described below, several methods for improving the LM model were proposed at the JVET conference.

[0053] MMLM-Mode: MMLM stands for Multi-Model LM Mode, where two linear models are used to derive chroma sample predictions. Reconstructed luminance values ​​are divided into two categories: one model is applied to each category. The derivation of the α and β parameters for each model is performed in the same way as in CCLM Mode; the reconstructed luminance (downsampled) used to derive the parameters is also correspondingly divided for each model.

[0054] MFLM mode: MFLM stands for Multi-Filter LM mode, where different filters are used to downsample the reconstructed brightness samples used in the prediction model. Four such filters are used, and the specific filter used is indicated / signaled in the bitstream.

[0055] LM Angle Prediction: In this mode, the MMLM mode and the non-LM mode are combined by averaging the prediction samples obtained from the two modes.

[0056] Multiple Neighbor-Based Linear Models (MNLMs) derive MMLMs using multiple neighbor sets to cover various linear relationships between luminance and chrominance samples in the CU. For example... Figure 11 The description proposes three MMLMs with different neighbor sets in MNLM:

[0057] MMLM: A, B, C, D (including the neighbors above and to the left)

[0058] The top MMLM numbers are: C, D, F, H (including only the top neighbors).

[0059] Left-side MMLM: A, B, E, G (including only left-side neighbors)

[0060] like Figure 11As shown, A is the second left neighbor. B is the first left neighbor. C is the first top neighbor. D is the second top neighbor. E is the third left neighbor. F is the third top neighbor. G is the fourth left neighbor. H is the fourth top neighbor.

[0061] The different CCLM prediction models in MNLM are listed in the table below:

[0062] Modes 0, 1, 2, and 3 use the same downsampling filter, but different neighbor sets are used for LM and MMLM derivation.

[0063] To reduce the complexity of CCLM parameter derivation, in the first embodiment, three sample pairs are used to derive parameters α and β. For example... Figure 12 As shown, the sample pair includes: the top sample in the left adjacent sample ( Rec' L [-1, 0], Rec C [-1,0]), the bottom sample in the left adjacent sample ( Rec' L [-1, H -1], Rec C [-1, H -1]), and the rightmost sample among the adjacent samples above ( Rec' L [ W -1, -1], Rec C [ W -1, -1]. W and H represent the width and height of the chroma block.

[0064] In another embodiment, such as Figure 13 As shown, the sample pair includes: the leftmost sample among the upper adjacent samples ( Rec' L [0, -1], Rec C [0, -1]), the bottom sample in the left adjacent sample ( Rec' L [-1, H -1], Rec C [-1, H -1]), and the rightmost sample among the adjacent samples above ( Rec' L [ W -1, -1], Rec C [ W -1, -1]).

[0065] Note that the selection of sample pairs is not limited to the mentioned embodiments. The three sample pairs can be any three sample pairs selected from the adjacent samples reconstructed from above or to the left, and the adjacent samples are not limited to only the top row or the left row.

[0066] In one embodiment, sample pairs with the maximum, median, and minimum luminance sample values ​​are identified by comparing luminance samples. The weighted average of the luminance sample values ​​of the maximum and median sample pairs is represented as x. B (as shown in equation (20)), and the weighted average of the chromaticity sample values ​​of the largest sample pair and the middle sample pair is expressed as y B (As shown in equation (22)); the weighted average of the brightness sample values ​​of the middle sample pair and the smallest sample pair is expressed as x A (as shown in equation (21)), and the weighted average of the chromaticity sample values ​​of the middle sample pair and the smallest sample pair is expressed as y A (As shown in equation (23)). Then use equation (2) to calculate the parameters α and β.

[0067] ; (20)

[0068] ; (twenty one)

[0069] ; (twenty two)

[0070] ; (twenty three)

[0071] Where x max It is the brightness sample value of the largest sample pair, x mid It is the brightness sample value of the intermediate sample pair, x min It is the brightness sample value of the smallest sample pair, y max It is the chromaticity sample value of the largest sample pair, y mid These are the chromaticity sample values ​​of the intermediate sample pairs, y min These are the chromaticity sample values ​​of the smallest sample pair; w1 + w2 = (1 < <N1),offset1 = 1<<(N1-1);w3 + w4 =(1<<N2),offset2 = 1<<(N2-1)。

[0072] Where w1 is the first weighting factor, w2 is the second weighting factor, w3 is the third weighting factor, and w4 is the fourth weighting factor; N1 is the first average value, N2 is the second average value; offset1 is the first offset factor, and offset2 is the second offset factor.

[0073] In one example where equal weighting is applied, w1 = 1, w2 = 1, w3 = 1, w4 = 1; N1 = 1, N2 = 1 and offset1 = 1, offset2 = 1.

[0074] In another example, w1 = 3, w2 = 1, w3 = 1, w4 = 3; N1 = 2, N2 = 2 and offset1 = 2, offset2 = 2.

[0075] In another embodiment, i, j, and k are used as indices for the three sample pairs, only in luma i and Luma j luma i and Luma k Two comparisons are performed between the two pairs of samples. Through these two comparisons, the three sample pairs can either be sorted entirely by luminance value or divided into two groups; one group contains two larger values ​​and the other contains one smaller value, or vice versa. When the values ​​are sorted entirely, the method described in the previous section can be used. When the sample pairs are divided into two groups, a weighted average is taken for the luminance and chrominance samples(s) within the same group (individual sample pairs within a group do not actually need to be weighted). For example, when there are two sample pairs in a group, the two luminance values ​​in the group are averaged with equal weights, and the two chrominance values ​​are also averaged with equal weights. Here, the weighted average is used as x. A x B y A and y B Use (2) to export CCLM parameters.

[0076] In another embodiment, sample pairs with the maximum luminance sample value and sample pairs with the minimum luminance sample value are identified by comparing luminance samples. The luminance sample value of the maximum sample pair is represented as x. B And the chromaticity sample value of the largest sample pair is represented as y. B The brightness sample value of the smallest sample pair is represented as x. A And the chromaticity sample value of the smallest sample pair is represented as y. A Then use equation (2) to calculate the parameters α and β.

[0077] Note that the method for deriving CCLM parameters is not limited to the mentioned embodiments. CCLM parameters can be derived in any way using the selected three sample pairs.

[0078] In the second embodiment, to reduce the complexity of deriving the CCLM parameters, four sample pairs are used to derive parameters α and β. For example... Figure 14As shown, the sample pair includes: the top sample in the left adjacent sample ( Rec' L [-1, 0], Rec C [-1, 0]), the leftmost sample among the adjacent samples above ( Rec' L [0, -1], Rec C [0, -1]), the bottom sample in the left adjacent sample ( Rec' L [-1, H -1], Rec C [-1, H -1]), and the rightmost sample among the adjacent samples above ( Rec' L [ W -1, -1], Rec C [ W -1, -1]).

[0079] In another embodiment, such as Figure 15 As shown, the sample pair includes: a quarter width starting from the leftmost sample in the adjacent sample above ( Rec' L [ W / 4, -1], Rec C [ W / 4, -1]), starting from the top sample in the left adjacent sample, one-quarter of the height ( Rec' L [-1, H / 4], Rec C [-1, H / 4]), the bottom sample in the left adjacent sample ( Rec' L [-1, H -1], Rec C [-1, H -1]), and the rightmost sample among the adjacent samples above ( Rec' L [ W -1, -1], Rec C [ W -1, -1]).

[0080] Note that the selection of sample pairs is not limited to the mentioned embodiments. The four sample pairs can be any four sample pairs selected from the adjacent samples reconstructed from above or to the left, and the adjacent samples are not limited to only the top row or the left row. For example, a set of sample pairs includes: one-quarter of the width starting from the leftmost sample in the top adjacent samples, one-quarter of the height starting from the top sample in the left adjacent samples, three-quarters of the width starting from the leftmost sample in the top adjacent samples, and three-quarters of the height starting from the top sample in the left adjacent samples.

[0081] Alternatively, another set of sample pairs includes: one-eighth of the width starting from the leftmost sample of the upper adjacent sample, three-eighths of the width starting from the leftmost sample of the upper adjacent sample, five-eighths of the width starting from the leftmost sample of the upper adjacent sample, and seven-eighths of the width starting from the leftmost sample of the upper adjacent sample.

[0082] Alternatively, another set of sample pairs includes: one-eighths of the height from the top sample in the left adjacent sample, three-eighths of the height from the top sample in the left adjacent sample, five-eighths of the height from the top sample in the left adjacent sample, and seven-eighths of the height from the top sample in the left adjacent sample.

[0083] In one embodiment, sample pairs with two larger luminance sample values ​​and two smaller luminance sample values ​​are identified by comparing luminance samples. The luminance sample values ​​of the two larger sample pairs are represented as x. B0 x B1 Furthermore, the chromaticity sample values ​​of two larger sample pairs are represented as y. B0 y B1 The brightness sample values ​​of two smaller sample pairs are represented as x. A0 x A1 And the chromaticity sample values ​​of the two smaller sample pairs are represented as y A0 y A1 As shown in the following equations, i.e., equations (24)-(27), then x A x B y A and y B Export as x A0 x A1 x B0 x B1 y A0 y A1 and y B0 y B1 The weighted average is then used. Then, the parameters α and β are calculated using equation (2).

[0084] (twenty four)

[0085] (25)

[0086] (26)

[0087] (27)

[0088] Where w1 + w2 = (1<<N1), offset1 = 1<<(N1-1); w3 + w4 = (1<<N2), offset2 = 1<<(N2-1). Here, w1 is the first weight factor, w2 is the second weight factor, w3 is the third weight factor, w4 is the fourth weight factor; N1 is the first average value, N2 is the second average value; offset1 is the first offset factor, and offset2 is the second offset factor.

[0089] In an example of applying equal weighting, w1 = 1, w2 = 1, w3 = 1, w4 = 1; N1 = 1, N2 = 1 and offset1 = 1, offset2 = 1.

[0090] In another example, w1 = 3, w2 = 1, w3 = 1, w4 = 3; N1 = 2, N2 = 2 and offset1 = 2, offset2 = 2.

[0091] In another embodiment, sample pairs having the maximum luminance sample value and the minimum luminance sample value respectively are identified by comparing luminance samples. The luminance sample value of the maximum sample pair is denoted as x B , and the chrominance sample value of the maximum sample pair is denoted as y B ; the luminance sample value of the minimum sample pair is denoted as x A , and the chrominance sample value of the minimum sample pair is denoted as y A . Then the parameters α and β are calculated using Equation (2).

[0092] Note that the method for deriving the CCLM parameters is not limited to the embodiments mentioned. Four selected sample pairs can be used in any way to derive the CCLM parameters.

[0093] Considering the specification and practice of the present invention disclosed herein, other embodiments of the present invention will be apparent to those skilled in the art. This application aims to cover any variations, uses, or adaptations of the present invention following its general principles, and includes such departures from the present disclosure as are known or customary in the art. The specification and examples are intended to be considered only as exemplary, and the true scope and spirit of the present invention are indicated by the appended claims.

[0094] It will be understood that the invention is not limited to the exact examples shown in the description and drawings above, and various modifications and changes can be made without departing from its scope. The scope of the invention is intended to be limited only by the appended claims.

[0095] In one or more examples, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functionality may be stored as one or more instructions or code on or transmitted through a computer-readable medium and executed by a hardware-based processing unit. A computer-readable medium may include a computer-readable storage medium, which corresponds to a tangible medium such as a data storage medium, or a communication medium, including, for example, any medium that facilitates the transfer of a computer program from one place to another according to a communication protocol. In this way, a computer-readable medium may generally correspond to (1) a non-transitory tangible computer-readable storage medium, or (2) a communication medium such as a signal or carrier wave. A data storage medium may be any available medium that can be accessed by one or more computers or one or more processors to retrieve instructions, code, and / or data structures for use in implementing the implementations described in this application. A computer program product may include a computer-readable medium.

[0096] Furthermore, the above methods can be implemented using a device comprising one or more circuits, including application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components. This device can be combined with other hardware or software components to use these circuits to perform the methods described above. Each module, submodule, unit, or subunit disclosed above can be implemented at least partially using one or more circuits.

[0097] Other embodiments of the invention will be apparent to those skilled in the art in light of the description and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow its general principles, and includes such deviations from this disclosure that are known or customary in the art. The description and examples are intended to be considered exemplary only, and the true scope and spirit of the invention are indicated by the appended claims.

[0098] It will be understood that the invention is not limited to the exact examples shown in the description and drawings above, and various modifications and changes can be made without departing from its scope. The scope of the invention is intended to be limited only by the appended claims.

Claims

1. A method for video encoding and decoding, comprising: By using a predetermined number of adjacent reconstructed luminance and chrominance samples in the codec unit (CU), the first parameter α and the second parameter β for the cross component linear model (CCLM) mode are derived. as well as The final chromaticity prediction value for the CU is generated by using the first parameter α and the second parameter β.

2. The method according to claim 1, wherein, Generating the final chromaticity prediction value for the chromaticity sample of the CU by using the first parameter α and the second parameter β includes: The final chromaticity prediction value is obtained using the following equation: Among them, pred C (x,y) is the final chromaticity prediction value for the chromaticity sample of the CU, rec L '(x,y) is the reconstructed brightness sample downsampled by the CU, where x represents the row index and y represents the column index.

3. The method according to claim 2, wherein, The first parameter α and the second parameter β for the CCLM mode are derived by using a predetermined number of adjacent reconstructed luminance and chrominance samples in the codec unit (CU): The first parameter α and the second parameter β are derived by using adjacent reconstructed chromaticity samples and their corresponding luminance samples, wherein each chromaticity sample and its corresponding luminance sample are called a sample pair.

4. The method according to claim 3, wherein, The first parameter α and the second parameter β are derived by using adjacent reconstructed chromaticity samples and their corresponding luminance samples, wherein each chromaticity sample and its corresponding luminance sample are referred to as the sample pair, which includes: The first parameter α and the second parameter β are obtained using the following equation: Among them, y B y represents the chromaticity sample value of the largest sample pair. A x is the chromaticity sample value of the smallest sample pair. B x is the brightness sample value of the largest sample pair. A The brightness sample value of the smallest sample pair.

5. The method according to claim 4, wherein, Deriving the first parameter α and the second parameter β using adjacent reconstructed chromaticity samples and their corresponding luminance samples includes: deriving the parameter α and the parameter β using three sample pairs; wherein the three sample pairs include one of the following sets of sample pairs: The top sample among the left adjacent samples, the bottom sample among the left adjacent samples, and the rightmost sample among the top adjacent samples; and The leftmost sample among the adjacent samples above, the bottom sample among the adjacent samples to the left, and the rightmost sample among the adjacent samples above.

6. The method according to claim 5, further comprising: x is obtained using the following equation. A x B y A and y B : ； ； ； ； Where, x max x is the brightness sample value of the largest sample pair. mid It is the brightness sample value of the intermediate sample pair, x min It is the brightness sample value of the smallest sample pair, y max It is the chromaticity sample value of the largest sample pair, y mid The chromaticity sample value of the intermediate sample pair, y min These are the chromaticity sample values ​​of the minimum sample pair; w1 + w2 = (1 << N1), offset1 = 1 << (N1-1); w3 + w4 = (1 << N2), offset2 = 1 << (N2-1); and Where w1 is the first weighting factor, w2 is the second weighting factor, w3 is the third weighting factor, and w4 is the fourth weighting factor; N1 is the first average value, N2 is the second average value; offset1 is the first offset factor, and offset2 is the second offset factor.

7. The method according to claim 5, further comprising: x is obtained as the brightness sample value of the largest sample pair. B ; Obtain the y value as the chromaticity sample value of the largest sample pair. B ; x is obtained as the brightness sample value of the minimum sample pair. A ;as well as Obtain the chromaticity sample value of the minimum sample pair. A .

8. A computing device, comprising: At least one processor; A non-transitory storage device coupled to one or more processors; as well as A plurality of programs stored in the non-transitory storage device, when executed by the processor, cause the computing device to perform actions including the following: By using a predetermined number of adjacent reconstructed luminance and chrominance samples in the codec unit (CU), the first parameter α and the second parameter β for the cross component linear model (CCLM) mode are derived. as well as The final chromaticity prediction value for the CU is generated by using the first parameter α and the second parameter β.

9. The computing device according to claim 8, wherein, Generating the final predicted chromaticity value for the chromaticity sample of the CU by using the first parameter α and the second parameter β includes: The final chromaticity prediction value is obtained using the following equation: Among them, pred C (x,y) is the final chromaticity prediction value for the chromaticity sample of the CU, rec L '(x,y) is the reconstructed brightness sample downsampled by the CU, where x represents the row index and y represents the column index.

10. The computing device according to claim 9, wherein, The first parameter α and the second parameter β for the CCLM mode are derived by using a predetermined number of adjacent reconstructed luminance and chrominance samples in the codec unit (CU): The first parameter α and the second parameter β are derived by using adjacent reconstructed chromaticity samples and their corresponding luminance samples, wherein each chromaticity sample and its corresponding luminance sample are called a sample pair.

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