Video coding using a cross-component linear model

Abstract

This invention provides a method and computing device for performing video coding using a cross-component linear model (CCLM). [Solution] The method includes deriving parameters α and β for the CCLM mode by using a predetermined number of adjacent reconstructed lumens and chroma samples in a coding unit (CU), and generating a final chroma predictor for the chroma samples of the CU using parameters α and β.

Description

Technical Field

[0001] This application claims the benefit of U.S. Provisional Application No. 62 / 790,459, filed Jan. 9, 2019. The entire disclosure of the foregoing application is incorporated herein by reference.

[0002] The present disclosure generally relates to video coding and compression. More specifically, this disclosure relates to systems and methods for performing video coding using a cross-component linear model. The method is described, in certain exemplary embodiments, by a final chroma predictor for chroma samples of a coding unit.

Background Art

[0003] This section provides background information related to the present disclosure. The information included in this section is not necessarily to be construed as prior art.

[0004] To compress video data, various video coding techniques may be used. Video coding is performed according to one or more video coding standards. For example, video coding standards include VVC (Versatile Video Coding), JEM (joint exploration test model), H.265 / HEVC (high-efficiency video coding), H.264 / AVC (advanced video coding), MPEG (moving picture experts group) coding, and the like. Video coding generally uses prediction methods that utilize redundancy present in video images or sequences (e.g., inter prediction, intra prediction, etc.). One important objective of video coding techniques is to compress video data in a form that uses a lower bitrate while avoiding or minimizing degradation to the quality of the video. To enable evolving video services, coding techniques with better compression efficiency are needed. [Overview of the Initiative]

[0005] This section provides an overview of the disclosure and does not constitute a comprehensive disclosure of its entire scope or all its characteristics.

[0006] According to a first aspect of this disclosure, a video coding method is performed in a computing device having one or more processors and one or more memories storing a plurality of programs 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 by using a predetermined number of adjacent reconstructed lumens and chroma samples in a coding unit (CU), and generating a final chroma predictor for the chroma samples of the CU by using the first parameter α and the second parameter β.

[0007] A second aspect of this disclosure provides a computing device. The computing device includes at least one processor, a non-temporary storage device connected to the one or more processors, and a plurality of programs stored in the non-temporary storage device, which, when executed by the processors, cause the computing device to perform operations, which include: deriving a first parameter α and a second parameter β relating to a cross-component linear model (CCLM) mode by using a predetermined number of adjacent reconstructed lumens and chroma samples in a coding unit (CU); and generating a final chroma predictor for the chroma samples of the CU by using the first parameter α and the second parameter β. [Brief explanation of the drawing]

[0008] A set of exemplary and non-limiting embodiments of the present disclosure are described below. Variations of structure, method, or function may be carried out by an ordinary person of the art in the relevant field based on the examples shown herein, and all such variations are within the scope of the present disclosure. Teachings of different embodiments may be combined with each other, but are not required, where there is no conflict. [Figure 1] Figure 1 is a block diagram illustrating an exemplary encoder that can be used with numerous video coding standards. [Figure 2] Figure 2 is a block diagram illustrating an exemplary decoder that can be used with numerous video coding standards. [Figure 3] Figure 3 is a flowchart of the video coding method. [Figure 4] Figure 4 shows an example of a lumen / chromen pixel sampling grid. [Figure 5] Figure 5 shows the locations of the samples used to derive α and β. [Figure 6] Figure 6 shows the linear derivation of α and β using the min-max method. [Figure 7] Figure 7 shows the LM_A mode. [Figure 8] Figure 8 shows the LM_A mode. [Figure 9] Figure 9 shows the lumens / chromens pixel sampling grid for the YUV4:2:2 format. [Figure 10] Figure 10 shows the lumens / chromens pixel sampling grid for the YUV4:2:4 format. [Figure 11] Figure 11 shows multiple neighbors in MMLM. [Figure 12] Figure 12 shows the locations of an example of three sample pairs. [Figure 13] Figure 13 shows the location of another example of the three sample pairs. [Figure 14] Figure 14 shows the locations of an example of four sample pairs. [Figure 15]Figure 15 shows the location of another example of the four sample pairs. [Modes for carrying out the invention]

[0009] The terms used in this disclosure are intended to illustrate specific examples, not to limit this disclosure. The singular forms “a,” “an,” and “the” used in this disclosure and the accompanying claims also refer to the plural form unless another meaning is clearly implied in the context. The terms “and / or” as used herein should be understood to refer to any or all possible combinations of one or more related listed items.

[0010] Here, terms such as “first,” “second,” and “third” may be used to indicate various types of information, and it should be understood that such information should not be limited by these terms. These terms are simply used to distinguish one category of information from another. For example, without departing from the scope of this disclosure, the first information may be referred to as the second information, and similarly, the second information may be referred to as the first information. The term “if” may be understood, as used herein, to mean “in the case,” “on the occasion,” or “depending on.”

[0011] Throughout this specification, any reference to “one embodiment,” “a certain embodiment,” “another embodiment,” or such in singular or plural form, means that one or more unique features, structures, or properties described in relation to a certain embodiment are included in at least one embodiment of this disclosure. Therefore, the appearance of the phrases “one embodiment,” “a certain embodiment,” “another embodiment,” or such in singular or plural form, in various places throughout this specification, does not necessarily refer to the same embodiment. Furthermore, unique features, structures, or properties in one or more embodiments may be combined in any suitable manner.

[0012] Conceptually, many video coding standards are similar, including those mentioned earlier in the "Background" section. For example, almost all video coding standards use block-based processing and share similar video coding block diagrams to achieve video compression.

[0013] Figure 1 shows a block diagram of an exemplary encoder 100 that can be used with a number of video coding standards. In encoder 100, a video frame is divided into multiple video blocks for processing. For each given video block, a prediction is made based on either an inter-prediction approach or an intra-prediction approach. In inter-prediction, one or more predictors are formed through motion estimation and motion compensation based on pixels from previously reconstructed frames. In intra-prediction, predictors are formed based on reconstructed pixels in the current frame. Through mode determination, the best predictor for predicting the current block is selected.

[0014] The prediction residual, representing the difference between the current video block and its predictor, is sent to the conversion circuit 102. Then, for entropy reduction, the conversion coefficients are sent from the conversion circuit 102 to the quantization circuit 104. The quantized coefficients are then supplied to the entropy coding circuit 106 to generate a compressed video bitstream. As shown in Figure 1, prediction-related information 110, such as video block partition information, motion vectors, reference picture index, and intra-prediction mode, from the inter-prediction circuit and / or intra-prediction circuit 112, is also supplied through the entropy coding circuit 106 and stored in the compressed video bitstream 114.

[0015] In encoder 100, decoder-related circuitry is also required to reconstruct pixels for prediction purposes. First, the prediction residual is reconstructed through inverse quantization 116 and inverse transform circuit 118. This reconstructed prediction residual is combined with block predictor 120 to generate unfiltered reconstructed pixels for the current video block.

[0016] In-loop filters are commonly used to improve coding efficiency and image quality. For example, deblocking filters are available in AVC and HEVC, as in the current version of VVC. HEVC defines an additional in-loop filter called SAO (sample adaptive offset) to further improve coding efficiency. In the current version of the VVC standard, another in-loop filter called ALF (adaptive loop filter) is being actively researched and is considered to have a good chance of being included in the final standard.

[0017] The operation of these in-loop filters is optional. Performing these operations helps improve coding efficiency and image quality. Alternatively, they may be turned off as a decision made by encoder 100 to save computational effort.

[0018] It should be noted that if these filter options are enabled by encoder 100, inter-predictions are based on filtered and reconstructed pixels, while intra-predictions are typically based on unfiltered and reconstructed pixels.

[0019] Figure 2 is a block diagram illustrating an exemplary decoder 200 that can be used with numerous video coding standards. This decoder 200 is similar to the reconstruction section present in the encoder 100 in Figure 1. In decoder 200 (Figure 2), the input video bitstream 201 is first decoded through entropy decoding 202 to derive the levels of quantized coefficients and prediction-related information. The levels of quantized coefficients are then processed through inverse quantization 204 and inverse transform 206 to obtain the reconstructed prediction residuals. The block predictor mechanism is implemented in the intra / intermode selector 212 and is configured to perform intra-prediction 208 or motion compensation 210 based on the decoded prediction information. The set of unfiltered reconstructed pixels is obtained by summing the reconstructed prediction residuals from the inverse transform 206 and the prediction output generated by the block predictor mechanism using the aggregater 214. When the in-loop filter is on, filtering operations are performed on these reconstructed pixels to derive the final reconstructed video for output.

[0020] To reduce cross-component redundancy, the prediction mode of a cross-component linear model (CCLM) is used in VVC. The YUV format 4:2:0 was used as a common test condition during VVC development, and the sampling grid for lumar and chromar samples for the YUV format 4:2:0 is shown in Figure 4. The coordinates of the lumar and chromar samples (downsampled lumar samples are also shown in Figure 4) are given. RecL'[x,y] represents the downsampled reconstructed lumar sample adjacent to the top and left, and RecC'[x,y] represents the reconstructed chromar sample adjacent to the top and left, where x and y represent the pixel indices as shown in the figure. This disclosure proposes several methods to reduce the complexity of deriving the CCLM parameters.

[0021] This disclosure generally relates to the coding (e.g., encoding and decoding) of video data. More specifically, this disclosure relates to a video coding method and a computing device for reducing cross-component redundancy of the video coding method. A CCLM predictor mode is used to predict chroma samples based on reconfigured luma samples of the same CU. The computing device includes at least one processor, a non-temporary storage device connected to the one or more processors, and a plurality of programs stored in the non-temporary storage device and, when executed by the processor, cause the computing device to perform the operation of the video coding method.

[0022] As shown in Figure 3, the video coding method includes at least the following steps:

[0023] Step 10: Deriving the first parameter α and the second parameter β for the CCLM mode by using a predetermined number of adjacent reconstituted lumens and chromates in the CU.

[0024] Step 20: Generation of the final chroma predictor for the chroma sample of CU using the first parameter α and the second parameter β.

[0025] In step 20, the final chroma predictor for the chroma sample of CU is generated using the following formula.

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[0026] Nod C (x,y) is the final chroma predictor for the chroma sample of CU, and rec L '(x,y) is a downsampled and reconstructed rumor sample of CU, where x is the row index and y is the column index.

[0027] Figure 5 shows the coordinates of the lumens sample and the chroma sample (downsampled lumens sample).

[0028] Parameter α and parameter β are derived by the following equation (referred to as the min-max method in the following section).

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[0029] Each chromatic sample and its corresponding chromatic sample are referred to as a sample pair. B is the chromatic sample value of the largest sample pair, and y A x is the chroma sample value of the smallest sample pair, and B is the rumor sample value of the largest sample pair, and x A This is the rumor sample value of the smallest sample pair.

[0030] As shown in Figure 6, the two points (a combination of lumens and chromens) (A,B) are the minimum and maximum values ​​in a set of adjacent lumens samples. Figure 6 is a diagram of the straight line between the minimum and maximum values ​​of the lumens when the parameters α and β of the linear model are obtained according to equation (2).

[0031] In Figure 5, Rec L '[x,y] represents the downsampled upper and left adjacent reconstructed lumens samples, Rec C[x, y] represents the upper and left adjacent reconstructed chroma samples, where x indicates the row index and y indicates the column index. Note that the square blocks in Figure 5 are the reconstructed luma samples corresponding to the positions of the luma samples depicted in Figure 4, and the circles in Figure 5 correspond to the positions of the chroma samples or downsampled luma samples depicted in Figure 4. For the square coding blocks, the min-max method is directly applied. For non-square coding blocks, first, the adjacent samples on the longer boundary are subsampled so that the number of samples is the same as that for the shorter boundary. Figure 5 shows the positions of the left and upper samples and the samples of the current block related to the CCLM mode.

[0032] The calculation of the min-max method is executed as part of the decoding process, not as a mere search operation of the encoder. Therefore, no syntax is used to convey the values of parameter α and parameter β to the decoder. Currently, Equation / Filter (3) is used as a luma downsampling filter to generate the downsampled luma samples. However, as shown from Equation (3) to (19), different equations / filters can be selected to generate the downsampled luma samples. Note that Equations (5) to (10) can be regarded as directly obtaining samples without downsampling processing. [Number]

[0033] Both the upper template and the left template can be used to calculate the coefficients of the linear model. Additionally, as an alternative, two other LM modes, LM_A and LM L although called, can also be used respectively. As shown in Figure 7, in the 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). As shown in Figure 8, LM LIn this mode, only the left template is used to calculate the coefficients of the linear model. To obtain more samples, the left template is expanded to (H+W). For non-rectangular blocks, the top template is expanded to W+W and the left template is expanded to H+H. If the top / left templates are unavailable, LM_A / LM L The mode is not checked or signaled. If there are not enough available samples, the template is augmented by copying the rightmost (for the top template) or bottommost (for the left template) sample to the nearest log2 number. In addition to the 4:2:0 YUV format, the codec also supports the 4:2:2 format (Figure 9) and the 4:4:4 format (Figure 10).

[0034] At the JVET meeting, several methods for improving LM mode were proposed, as follows:

[0035] MMLM mode: MMLM corresponds to the LM mode of multi-models, where two linear models are used to derive predictions for chroma samples. The reconstructed ruma values ​​are divided into two categories, with one model assigned to each category. The derivation of the α and β parameters for each model is performed as CCLM mode, but the reconstructed ruma (downsampled) used to derive the parameters is also divided according to each model.

[0036] MFLM mode: MFLM is a multi-filter LM mode in which different filters are used to downsample the reconstructed lumens used in the predictive model. Four such filters are used, and the specific filter used in the bitstream is indicated / signaled.

[0037] 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.

[0038] The MNLM (Multiple Neighbor-based Linear Model) uses multiple neighbor sets to derive MMLM and covers various linear relationships between lumens and chromac samples of CU. As shown in Figure 11, three MNLMs with different neighbor sets have been proposed for MMLM.

[0039] MMLM: A, B, C, D (including top and left neighbors)

[0040] The above MMLM:C, D, F, H (including only the above neighbors)

[0041] Left MMLM: A, B, E, G (includes only the left neighbor)

[0042] As shown in Figure 11, A is the second neighbor to the left. B is the first neighbor to the left. C is the first neighbor above. D is the second neighbor above. E is the third neighbor to the left. F is the third neighbor above. G is the fourth neighbor to the left. H is the fourth neighbor above.

[0043] The different CCLM prediction modes for MNLM are listed in the table below. [Table 1]

[0044] Modes 0, 1, 2, and 3 use the same downsampling filter but employ different neighbor sets for LM and MMLM derivations.

[0045] To reduce the complexity of deriving the CCLM parameters, in the first embodiment, three sample pairs are used to derive parameters α and β. As shown in Figure 12, the sample pairs are the topmost sample (Rec') of the adjacent samples on the left. L [-1,0],Rec C[-1,0]) and the lowest sample among the adjacent samples on the left (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]) and includes, where W and H indicate the width and height of the chroma block.

[0046] In another embodiment, as shown in Figure 13, the sample pair is the leftmost sample (Rec') of the adjacent samples above. L [0,-1],Rec C [0,-1]) and the lowest sample among the adjacent samples on the left (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]) and includes

[0047] The selection of sample pairs is not limited to the embodiments described above. The three sample pairs may be any three sample pairs selected from the reconfigured adjacent samples above or to the left, and the adjacent samples are not limited to just one line above or one line to the left.

[0048] In one embodiment, sample pairs having the maximum ruma sample value, the intermediate sample value, and the minimum ruma sample value are identified through ruma sample comparison. The weighted average of the ruma sample values ​​of the maximum and intermediate sample pairs is x B As shown in equation (21), the weighted average of the chroma sample values ​​of the maximum and intermediate sample pairs is y B This is shown (as shown in equation (23)). Also, the weighted average of the lumens sample values ​​of the intermediate and minimum sample pairs is x A As shown in equation (20), the weighted average of the chroma sample values ​​of the intermediate and minimum sample pairs is y AThis is shown (as shown in equation (22)). Then, using equation (2), the parameters α and β are calculated.

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[0049] x max is the rumor sample value of the largest sample pair, and x mid x is the rumor sample value of the intermediate sample pair, min is the lumen sample value of the smallest sample pair, and y max is the chromatic sample value of the largest sample pair, and y mid is the chroma sample value of the intermediate sample pair, and y min w1+w2=(1< <N1)、offset1=1<<(N1-1)であり、w3+w4=(1<<N2)、offset2=1<<(N2-1)である。

[0050] w1 is the first weighting coefficient, w2 is the second weighting coefficient, w3 is the third weighting coefficient, and w4 is the fourth weighting coefficient. Also, N1 is the first mean value, and N2 is the second mean value. Furthermore, offset1 is the first offset coefficient, and offset2 is the second offset coefficient.

[0051] 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.

[0052] In yet another example, w1=3, w2=1, w3=1, w4=3, N1=2, N2=2, and offset1=2, offset2=2.

[0053] In yet another example, w1=3, w2=1, w3=1, w4=3, N1=2, N2=2, and offset1=2, offset2=2.

[0054] In yet another embodiment, i, j, and k are used as indices for three sample pairs, and luma i and luma j And, luma i and luma k Only two comparisons are made: and . These two comparisons allow the three sample pairs to be completely sorted by their lumen values, or to be divided into two groups, one containing the two larger values ​​and the other containing the smaller values, or vice versa. If the values ​​are completely sorted, the method described in the previous section can be used. If the sample pairs are divided into two groups, the lumen and chroma samples within the same group are weighted and averaged (a single sample pair within a group does not practically require a weighted average). For example, if there are two sample pairs in one group, the two lumen values ​​in one group are weighted and averaged equally, while the two chroma values ​​are also weighted and averaged equally. Here, in order to derive the CCLM parameters using (2), the weighted averaged values ​​are x A , x B , y A and y B It is used as such.

[0055] In yet another embodiment, a sample pair having the largest ruma sample value and a sample pair having the smallest ruma sample value are identified through a comparison of the ruma samples. The ruma sample value of the largest sample pair is x B This indicates that the chroma sample value of the largest sample pair is y BThis indicates that the lumens sample value of the smallest sample pair is x A This indicates that the chroma sample value of the smallest sample pair is y A This is shown. Then, the parameters α and β are calculated using equation (2).

[0056] Furthermore, the method for deriving the CCLM parameters is not limited to the embodiments described above. The three selected sample pairs can be used in any way to derive the CCLM parameters.

[0057] In the second embodiment, to reduce the complexity of deriving CCLM, parameters α and β are derived using four sample pairs. As shown in Figure 14, the sample pairs are the topmost sample (Rec') of the adjacent samples on the left. L [-1,0],Rec C [-1,0]) and the leftmost sample among the adjacent samples above (Rec' L [0,-1],Rec C [0,-1]) and the lowest sample among the adjacent samples on the left (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]) and includes

[0058] In another embodiment, as shown in Figure 15, the sample pair is one-quarter of the width of the leftmost sample among the adjacent samples (Rec' L [W / 4,-1],Rec C [W / 4,-1]) and the quarter of the width of the topmost sample among the adjacent samples to the left (Rec' L [-1,H / 4],Rec C [-1,H / 4]) and the bottommost sample among the adjacent samples on the left (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]) and includes

[0059] The selection of sample pairs is not limited to the embodiments described above. The four sample pairs can be any four sample pairs selected from the reconfigured adjacent samples above or to the left, and the adjacent samples are not limited to just one line above or one line to the left. For example, a set of sample pairs may include one-quarter of the width of the leftmost sample among the adjacent samples above, one-quarter of the width of the topmost sample among the adjacent samples to the left, three-quarters of the width of the leftmost sample among the adjacent samples above, and three-quarters of the width of the topmost sample among the adjacent samples to the left.

[0060] Alternatively, another set of sample pairs includes one-eighth of the width of the leftmost sample among the adjacent samples above, three-eighths of the width of the leftmost sample among the adjacent samples above, five-eighths of the width of the leftmost sample among the adjacent samples above, and seven-eighths of the width of the leftmost sample among the adjacent samples above.

[0061] Alternatively, another set of sample pairs includes one-eighth of the height of the topmost sample among the left adjacent samples, three-eighths of the height of the topmost sample among the left adjacent samples, five-eighths of the height of the topmost sample among the left adjacent samples, and seven-eighths of the height of the topmost sample among the left adjacent samples.

[0062] In one embodiment, a sample pair having two larger ruma-sample values ​​and two smaller ruma-sample values ​​is identified through a comparison of ruma-samples. The ruma-sample values ​​of the two larger sample pairs are x B0 , x B1and are shown, and the chroma sample values of the two larger maximum sample pairs are y B0 , y B1 and are shown. The luma sample values of the two smaller sample pairs are x A0 , x A1 and are shown, and the chroma sample values of the two smaller minimum sample pairs are y A0 , y A1 and are shown. And, as shown in the following equations, equations (24)-(27), x A , x B , y A and y B are derived as the weighted averages of x A0 , x A1 , x B0 , x B1 , y A0 , y A1 and y B0 , y B1 . And the parameter α and the parameter β are calculated using equation (2). [Number] [Number] [Number] [Number]

[0063] w1 + w2 = (1 << N1), offset1 = 1 << (N1 - 1). w3 + w4 = (1 << N2), offset2 = 1 << (N2 - 1). w1 is the first weighting coefficient, w2 is the second weighting coefficient, w3 is the third weighting coefficient, and w4 is the fourth weighting coefficient. Also, N1 is the first average value, and N2 is the second average value. Also, offset1 is the first offset coefficient, and offset2 is the second offset coefficient.

[0064] 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.

[0065] In yet another example, w1=3, w2=1, w3=1, w4=3, N1=2, N2=2, and offset1=2, offset2=2.

[0066] In another embodiment, a sample pair having the largest ruma sample value and the smallest ruma sample value is identified through a comparison of ruma samples. The ruma sample value of the largest sample pair is x B This indicates that the chroma sample value of the largest sample pair is y B This indicates that the rumor sample value of the smallest sample pair is x A This indicates that the chroma sample value of the smallest sample pair is y A This is shown. Then, the parameters α and β are calculated using equation (2).

[0067] Furthermore, the method for deriving the CCLM parameters is not limited to the embodiments described above. The four selected sample pairs can be used in any way to derive the CCLM parameters.

[0068] Other embodiments of the present invention will be apparent to those skilled in the art by considering this specification and the practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention in accordance with its general principles, including deviations from this disclosure that fall within the scope of known or customary practices in the art. This specification and examples are intended to be considered merely illustrative and are in accordance with the true scope and spirit of the invention as set forth by the following claims.

[0069] It will be acknowledged that the present invention is not limited to the specific examples described above and shown in the accompanying drawings, and that various modifications and changes can be made without departing from its scope. The scope of the present invention is intended to be limited only by the appended claims.

[0070] In one or more examples, the described functions may be implemented in hardware, software, firmware, or a combination thereof. If implemented in software, the functions may be stored as one or more instructions or codes in a computer-readable medium, or transmitted through such a medium, and executed by a hardware-based processing unit. Computer-readable medium includes computer-readable storage mediums corresponding to tangible media such as data storage media, and communication media including any medium that facilitates the transmission of computer programs from one place to another, for example, according to a communication protocol. Thus, computer-readable medium may generally correspond to (1) non-temporary, tangible computer-readable storage medium, or (2) communication media such as signals, carrier waves, etc. Data storage medium may be any available medium accessible by one or more computers or one or more processors to obtain instructions, codes and / or data structures for implementations described herein. Computer program products may include computer-readable medium.

[0071] Furthermore, the above method may be implemented using a device that includes one or more circuits, such as ASICs (application-specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), controllers, microcontrollers, microprocessors, or other electronic components. The device may use circuits combined with other hardware or software components for performing the above method. Each of the above modules, submodules, units, or subunits may be implemented at least partially using one or more circuits.

[0072] Other embodiments of the present invention will be apparent to those skilled in the art by considering this specification and the practices of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention in accordance with its general principles, including deviations from this disclosure that fall within the scope of known or customary practices in the art. This specification and examples are intended to be considered merely illustrative and are in accordance with the true scope and spirit of the invention as set forth by the following claims.

[0073] It will be acknowledged that the present invention is not limited to the specific examples described above and shown in the accompanying drawings, and that various modifications and changes can be made without departing from its scope. The scope of the present invention is intended to be limited only by the appended claims.

Claims

1. The first parameter α and the second parameter β for the cross-component linear model (CCLM) mode are derived by using a predetermined number of adjacent reconstructed lumens and chromens in the coding unit (CU), The first parameter α and the second parameter β are used to generate a final chroma predictor for the chroma sample of the CU, A method for video coding that includes the following features.

2. Using the first parameter α and the second parameter β, the final chroma predictor for the chroma sample of the CU is generated as follows: The final chroma predictor is obtained using the following equation: [Math 1] Equipped with, pred Ｃ (x, y) is the final chroma predictor for the chroma sample of the CU, and rec Ｌ '(x, y) is a downsampled and reconstructed lumen sample of the CU, where x is the row index and y is the column index. The method according to claim 1.

3. Deriving the first parameter α and the second parameter β for the CCLM mode by using a predetermined number of adjacent reconstructed lumens and chromens in a coding unit (CU) is: The first parameter α and the second parameter β are derived by using adjacent reconstructed chromatic samples and their corresponding lumar samples, wherein each chromatic sample and its corresponding lumar sample is referred to as a sample pair. The method according to claim 2, comprising:

4. Each chromatic sample and its corresponding lunar sample are referred to as the sample pair, and the first parameter α and the second parameter β can be derived by using adjacent reconstructed chromatic samples and their corresponding lunar samples. The first parameter α and the second parameter β are obtained using the following equation: [Math 2] Equipped with, y Ｂ is the chromatic sample value of the largest sample pair, and y Ａ x is the chroma sample value of the smallest sample pair, Ｂ x is the rumor sample value of the largest sample pair, Ａ This is the rumor sample value of the smallest sample pair. The method according to claim 3.

5. The first parameter α and the second parameter β can be derived by using adjacent reconstructed chromatic samples and their corresponding chromatic samples. Three sample pairs are used to derive the aforementioned parameters α and β. Equipped with, The three sample pairs mentioned above are, A sample pair set consisting of the uppermost sample among the adjacent samples to the left, the lowermost sample among the adjacent samples to the left, and the rightmost sample among the adjacent samples above, A sample pair set consisting of the leftmost sample among the adjacent samples above, the bottommost sample among the adjacent samples to the left, and the rightmost sample among the adjacent samples above, Includes one of the sample sets, The method according to claim 4.

6. Obtain x using the following formula Ａ、 x Ｂ , y Ａ、 and y Ｂ to obtain [Math 3] Furthermore, x ｍａｘ x is the rumor sample value of the largest sample pair mentioned above, ｍｉｄ is the rumor sample value of the intermediate sample pair, and x ｍｉｎ is the lumar sample value of the smallest sample pair, and y ｍａｘ is the chromatic sample value of the largest sample pair, and y ｍｉｄ is the chromatic sample value of the aforementioned intermediate sample pair, and y ｍｉｎ The chromatic sample values ​​of the smallest sample pair are as follows: w1 + w2 = (1 << N1), offset1 = 1 << (N1 - 1), w3 + w4 = (1 << N2), offset2 = 1 << (N2 - 1), w1 is the first weighting coefficient, w2 is the second weighting coefficient, w3 is the third weighting coefficient, w4 is the fourth weighting coefficient, N1 is the first mean value, N2 is the second mean value, offset1 is the first offset coefficient, and offset2 is the second offset coefficient. The method according to claim 5.

7. x is the lumen sample value of the largest sample pair. Ｂ To obtain, The chromatic sample value of the largest sample pair is y Ｂ To obtain, x is the lumar sample value of the smallest sample pair. Ａ To obtain, The chromatic sample value of the smallest sample pair is y Ａ To obtain, The method according to claim 5, further comprising:

8. Deriving the parameters α and β by using adjacent reconstructed chromatic samples and their corresponding chromatic samples is possible. To derive the aforementioned parameters α and β, four sample pairs are used. Equipped with, The four sample pairs mentioned above are: A sample pair set consisting of the uppermost sample among the adjacent samples on the left, the leftmost sample among the adjacent samples above, the lowermost sample among the adjacent samples on the left, and the rightmost sample among the adjacent samples above, A sample pair set comprising one-quarter of the width of the leftmost sample among the adjacent samples above, one-quarter of the width of the topmost sample among the adjacent samples to the left, the bottommost sample among the adjacent samples to the left, and the rightmost sample among the adjacent samples above, A sample pair set comprising one-quarter of the width of the leftmost sample among the adjacent samples above, one-quarter of the width of the topmost sample among the adjacent samples to the left, three-quarters of the width of the leftmost sample among the adjacent samples above, and three-quarters of the width of the topmost sample among the adjacent samples to the left, A sample pair set comprising one-eighth of the width of the leftmost sample among the adjacent samples, three-eighths of the width of the leftmost sample among the adjacent samples, five-eighths of the width of the leftmost sample among the adjacent samples, and seven-eighths of the width of the leftmost sample among the adjacent samples, A sample pair set comprising one-eighth of the height of the uppermost sample among the adjacent samples to the left, three-eighths of the height of the uppermost sample among the adjacent samples to the left, five-eighths of the height of the uppermost sample among the adjacent samples to the left, and seven-eighths of the height of the uppermost sample among the adjacent samples to the left, Includes one of the sample sets, The method according to claim 4.

9. Using the following equation, x Ａ、 x Ｂ , y Ａ and y Ｂ To obtain [Math 4] Furthermore, w1 + w2 = (1 << N1), offset1 = 1 << (N1 - 1), and w3 + w4 = (1 << N2), offset2 = 1 << (N2 - 1), The lumen sample value for two larger sample pairs is x Ｂ０ , x Ｂ１ This indicates that the chromatic sample values ​​for the two largest sample pairs are y Ｂ０ , y Ｂ１ This indicates that the lumens sample value for the two smaller sample pairs is x Ａ０ , x Ａ１ This indicates that the chromatic sample value for the two smallest sample pairs is y Ａ０ , y Ａ１ It was shown that, w1 is the first weighting coefficient, w2 is the second weighting coefficient, w3 is the third weighting coefficient, w4 is the fourth weighting coefficient, N1 is the first mean value, N2 is the second mean value, offset1 is the first offset coefficient, and offset2 is the second offset coefficient. The method according to claim 8.

10. A computing device, At least one processor, A non-temporary storage device connected to one or more of the aforementioned processors, Multiple programs, stored in the non-temporary storage device and, when executed by the processor, cause the computing device to perform the following actions: Prepare, The aforementioned operation is, The first parameter α and the second parameter β for the cross-component linear model (CCLM) mode are derived by using a predetermined number of adjacent reconstructed lumens and chromens in the coding unit (CU), The first parameter α and the second parameter β are used to generate a final chroma predictor for the chroma sample of the CU, Equipped with, Computing device.

11. Using the first parameter α and the second parameter β, the final predictor of the chroma for the chroma sample of the CU is: The final chroma predictor is obtained using the following equation: [Math 5] Equipped with, pred Ｃ (x, y) is the final chroma predictor for the chroma sample of the CU, and rec Ｌ '(x, y) is a downsampled and reconstructed lumen sample of the CU, where x is the row index and y is the column index. The computing device according to claim 10.

12. Deriving the first parameter α and the second parameter β for the CCLM mode by using a predetermined number of adjacent reconstructed lumens and chromens in a coding unit (CU) is: Each chromatic sample and its corresponding lunar sample are referred to as a sample pair, and the first parameter α and the second parameter β are derived by using adjacent reconstructed chromatic samples and their corresponding lunar samples. The computing device according to claim 11, comprising:

13. Each chromatic sample and its corresponding lunar sample are referred to as the sample pair, and the first parameter α and the second parameter β can be derived by using adjacent reconstructed chromatic samples and their corresponding lunar samples. The first parameter α and the second parameter β are obtained using the following equation: [Math 6] Equipped with, y Ｂ is the chromatic sample value of the largest sample pair, and y Ａ x is the chroma sample value of the smallest sample pair, Ｂ x is the rumor sample value of the largest sample pair, Ａ This is the rumor sample value of the smallest sample pair. The computing device according to claim 12.

14. The first parameter α and the second parameter β can be derived by using adjacent reconstructed chromatic samples and their corresponding chromatic samples. Three sample pairs are used to derive the aforementioned parameters α and β. Equipped with, The three sample pairs mentioned above are, A sample pair consisting of the uppermost sample among the adjacent samples to the left, the lowermost sample among the adjacent samples to the left, and the rightmost sample among the adjacent samples above, A sample pair consisting of the leftmost sample among the adjacent samples above, the bottommost sample among the adjacent samples to the left, and the rightmost sample among the adjacent samples above, Includes one of the sample pairs, The computing device according to claim 13.

15. The aforementioned act is, Using the following equation, x Ａ , x Ｂ , y Ａ and y Ｂ To obtain [Number 7] Furthermore, x ｍａｘ x is the rumor sample value of the largest sample pair mentioned above, ｍｉｄ is the rumor sample value of the intermediate sample pair, and x ｍｉｎ is the lumar sample value of the smallest sample pair, and y ｍａｘ is the chromatic sample value of the largest sample pair, and y ｍｉｄ is the chromatic sample value of the aforementioned intermediate sample pair, and y ｍｉｎ The chromatic sample values ​​of the smallest sample pair are as follows: w1 + w2 = (1 << N1), offset1 = 1 << (N1 - 1), w3 + w4 = (1 << N2), offset2 = 1 << (N2 - 1), w1 is the first weighting coefficient, w2 is the second weighting coefficient, w3 is the third weighting coefficient, w4 is the fourth weighting coefficient, N1 is the first mean value, N2 is the second mean value, offset1 is the first offset coefficient, and offset2 is the second offset coefficient. The computing device according to claim 14.

16. The aforementioned act is, x is the lumen sample value of the largest sample pair. Ｂ To obtain, The chromatic sample value of the largest sample pair is y Ｂ To obtain, x is the lumar sample value of the smallest sample pair. Ａ To obtain, The chromatic sample value of the smallest sample pair is y Ａ To obtain, The computing device according to claim 14, further comprising:

17. Deriving the parameters α and β by using adjacent reconstructed chromatic samples and their corresponding chromatic samples is possible. To derive the aforementioned parameters α and β, four sample pairs are used. Equipped with, The four sample pairs mentioned above are: A sample pair set consisting of the uppermost sample among the adjacent samples on the left, the leftmost sample among the adjacent samples above, the lowermost sample among the adjacent samples on the left, and the rightmost sample among the adjacent samples above, A sample pair set comprising one-quarter of the width of the leftmost sample among the adjacent samples above, one-quarter of the width of the topmost sample among the adjacent samples to the left, the bottommost sample among the adjacent samples to the left, and the rightmost sample among the adjacent samples above, A sample pair set comprising one-quarter of the width of the leftmost sample among the adjacent samples above, one-quarter of the width of the topmost sample among the adjacent samples to the left, three-quarters of the width of the leftmost sample among the adjacent samples above, and three-quarters of the width of the topmost sample among the adjacent samples to the left, A sample pair set comprising one-eighth of the width of the leftmost sample among the adjacent samples, three-eighths of the width of the leftmost sample among the adjacent samples, five-eighths of the width of the leftmost sample among the adjacent samples, and seven-eighths of the width of the leftmost sample among the adjacent samples, A sample pair set comprising one-eighth of the height of the uppermost sample among the adjacent samples to the left, three-eighths of the height of the uppermost sample among the adjacent samples to the left, five-eighths of the height of the uppermost sample among the adjacent samples to the left, and seven-eighths of the height of the uppermost sample among the adjacent samples to the left, Includes one of the sample sets, The computing device according to claim 13.

18. The aforementioned act is, Using the following equation, x Ａ , x Ｂ , y Ａ and y Ｂ To obtain [Number 8] Furthermore, w1 + w2 = (1 << N1), offset1 = 1 << (N1 - 1), and w3 + w4 = (1 << N2), offset2 = 1 << (N2 - 1), The lumen sample value for two larger sample pairs is x Ｂ０ , x Ｂ１ This indicates that the chromatic sample values ​​for the two largest sample pairs are y Ｂ０ , y Ｂ１ This indicates that the lumens sample value for the two smaller sample pairs is x Ａ０ , x Ａ１ This indicates that the chromatic sample value for the two smallest sample pairs is y Ａ０ , y Ａ１ It was shown that, w1 is the first weighting coefficient, w2 is the second weighting coefficient, w3 is the third weighting coefficient, w4 is the fourth weighting coefficient, N1 is the first mean value, N2 is the second mean value, offset1 is the first offset coefficient, and offset2 is the second offset coefficient. The computing device according to claim 17.

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