WO2020094058A1 - Position dependent intra prediction - Google Patents

Position dependent intra prediction Download PDF

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Publication number
WO2020094058A1
WO2020094058A1 PCT/CN2019/115992 CN2019115992W WO2020094058A1 WO 2020094058 A1 WO2020094058 A1 WO 2020094058A1 CN 2019115992 W CN2019115992 W CN 2019115992W WO 2020094058 A1 WO2020094058 A1 WO 2020094058A1
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Prior art keywords
samples
chroma
block
neighboring
video
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PCT/CN2019/115992
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English (en)
French (fr)
Inventor
Kai Zhang
Li Zhang
Hongbin Liu
Jizheng Xu
Yue Wang
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Beijing ByteDance Network Technology Co Ltd
ByteDance Inc
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Beijing ByteDance Network Technology Co Ltd
ByteDance Inc
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Application filed by Beijing ByteDance Network Technology Co Ltd, ByteDance Inc filed Critical Beijing ByteDance Network Technology Co Ltd
Priority to EP19881776.9A priority Critical patent/EP3861736A4/en
Priority to KR1020217008482A priority patent/KR102653562B1/ko
Priority to CN201980072612.2A priority patent/CN112997488B/zh
Priority to JP2021523502A priority patent/JP7596264B2/ja
Publication of WO2020094058A1 publication Critical patent/WO2020094058A1/en
Priority to US16/940,826 priority patent/US11019344B2/en
Anticipated expiration legal-status Critical
Priority to JP2023065495A priority patent/JP7832143B2/ja
Priority to JP2025000097A priority patent/JP2025036709A/ja
Ceased legal-status Critical Current

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Definitions

  • This patent document relates to video processing techniques, devices and systems.
  • CCLM cross-component linear model
  • the described methods may be applied to both the existing video coding standards (e.g., High Efficiency Video Coding (HEVC) ) and future video coding standards (e.g., Versatile Video Coding (VVC) ) or codecs.
  • HEVC High Efficiency Video Coding
  • VVC Versatile Video Coding
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model based on selected chroma samples based on positions of the chroma samples, wherein the selected chroma samples are selected from a group of neighboring chroma samples, and performing the conversion based on the determining.
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a current video block, a group of neighboring chroma samples used to derive a set of values for parameters of a linear model, wherein a width and a height of the current video block is W and H, respectively, and wherein the group of neighboring chroma samples comprises at least one sample that is located beyond 2 ⁇ W above neighboring chroma samples or 2 ⁇ H left neighboring chroma samples; and performing, based on the linear model, a conversion between the current video block and a coded representation of a video including the current video block.
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes: determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, multiple sets of parameters, wherein each set of parameters defines a cross-component linear model (CCLM) and is derived from a corresponding group of chroma samples at corresponding chroma sample positions; determining, based on the multiple sets of parameters, parameters for a final CCLM; and performing the conversion based on the final CCLM.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a conversion between a current video block of a video and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on maximum and minimum values of chroma and luma samples of N groups of chroma and luma samples selected from neighboring luma and chroma samples of the current video block; and performing the conversion using the CCLM.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model that are completely determinable by two chroma samples and corresponding two luma samples; and performing the conversion based on the determining.
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, a final prediction P (x, y) of a chroma sample at a position (x, y) in the current video block as a combination of prediction results of multiple cross-component linear models (MCCLMs) , wherein the MCCLMs are selected based on the position (x, y) of the chroma sample; and performing the conversion based on the final prediction.
  • MCLMs cross-component linear models
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes performing, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, a first determination regarding whether a first cross-component linear model (CCLM) that uses only left-neighboring samples is used for predicting samples of the current video block and/or a second determination regarding whether a second cross-component linear model (CCLM) that uses only above-neighboring samples is used for predicting samples of the current video block; and performing the conversion based on the first determination and/or the second determination.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a conversion between a current video block of a video and a coded representation of the video, a context that is used to code a flag using arithmetic coding in the coded representation of the current video block, wherein the context is based on whether a top-left neighboring block of the current video block is coded using a cross-component linear model (CCLM) prediction mode; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a conversion between a current video block of a video and a coded representation of the video, parameters for a linear model prediction or cross-color component prediction based on refined chroma and luma samples of the current video block; and performing the conversion based on the determining.
  • the disclosed technology may be used to provide a method for video processing.
  • the method includes determining, for a conversion between a current video block of a video and a coded representation of the video, parameters for a linear model prediction or cross-color component prediction based on a main color component and a dependent color component, the main color component selected as one of a luma color component and a chroma color component and the dependent color component selected as the other of the luma color component and the chroma color component; and performing the conversion based on the determining.
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: performing downsampling on chroma and luma samples of a neighboring block of the current video block; determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of cross-component linear model (CCLM) based on the downsampled chroma and luma samples obtained from the downsampling; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on two or more chroma samples from a group of neighboring chroma samples, wherein the two or more chroma samples are selected based on a coding mode of the current video block; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of cross-component linear model (CCLM) based on chroma samples that are selected based on H available left-neighboring samples of the current video block; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on two or four chroma samples and/or corresponding luma samples; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: selecting, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, chroma samples based on a position rule, the chroma samples used to derive parameters of a cross-component linear model (CCLM) ; and performing the conversion based on the determining, wherein the position rule specifies to select the chroma samples that are located within an above row and/or a left column of the current video block.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, positions at which luma samples are downsampled, wherein the downsampled luma samples are used to determine parameters of a cross-component linear model (CCLM) based on chroma samples and downsampled luma samples, wherein the downsampled luma samples are at positions corresponding to positions of the chroma samples that are used to derive the parameters of the CCLM; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, a method to derive parameters of a cross-component linear model (CCLM) using chroma samples and luma samples based on a coding condition associated with the current video block; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, whether to derive maximum values and/or minimum values of a luma component and a chroma component that are used to derive parameters of a cross-component linear model (CCLM) based on availability of a left-neighboring block and an above-neighboring block of the current video block; and performing the conversion based on the determining.
  • CCLM cross-component linear model
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises determining, for a conversion between a current video block of a video and a coded representation of the video, parameters of a coding tool using a linear model based on selected neighboring samples of the current video block and corresponding neighboring samples of a reference block; and performing the conversion based on the determining.
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises: determining, for a conversion between a current video block of a video and a coded representation of the video, parameters of a local illumination compensation (LIC) tool based on N neighboring samples of the current video block and N corresponding neighboring samples of a reference block, wherein the N neighboring samples of the current video block are selected based on positions of the N neighboring samples; and performing the conversion based on the determining, wherein the LIC tool uses a linear model of illumination changes in the current video block during the conversion.
  • LIC local illumination compensation
  • the disclosed technology may be used to provide a method for video processing.
  • the method comprises determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on chroma samples and corresponding luma samples; and performing the conversion based on the determining, wherein some of the chroma samples are obtained by a padding operation and the chroma samples and the corresponding luma samples are grouped into two arrays G0 and G1, each array including two chroma samples and corresponding luma samples.
  • CCLM cross-component linear model
  • a device that is configured or operable to perform the above-described method.
  • the device may include a processor that is programmed to implement this method.
  • a video decoder apparatus may implement a method as described herein.
  • FIG. 1 shows an example of locations of samples used for the derivation of the weights of the linear model used for cross-component prediction.
  • FIG. 2 shows an example of classifying neighboring samples into two groups.
  • FIG. 3A shows an example of a chroma sample and its corresponding luma samples.
  • FIG. 3B shows an example of down filtering for the cross-component linear model (CCLM) in the Joint Exploration Model (JEM) .
  • CCLM cross-component linear model
  • JEM Joint Exploration Model
  • FIGS. 4A and 4B show examples of only top-neighboring and only left-neighboring samples used for prediction based on a linear model, respectively.
  • FIG. 5 shows an example of a straight line between minimum and maximum luma values as a function of the corresponding chroma samples.
  • FIG. 6 shows an example of a current chroma block and its neighboring samples.
  • FIG. 7 shows an example of different parts of a chroma block predicted by a linear model using only left-neighboring samples (LM-L) and a linear model using only above-neighboring samples (LM-A) .
  • FIG. 8 shows an example of a top-left neighboring block.
  • FIG. 10 shows an example of left and below-left columns and above and above-right rows relative to a current block.
  • FIG. 11 shows an example of a current block and its reference samples.
  • FIG. 12 shows examples of two neighboring samples when both left and above neighboring reference samples are available.
  • FIG. 13 shows examples of two neighboring samples when only above neighboring reference samples are available.
  • FIG. 14 shows examples of two neighboring samples when only left neighboring reference samples are available.
  • FIG. 15 shows examples of four neighboring samples when both left and above neighboring reference samples are available.
  • FIG. 16 shows an example of lookup tables used in LM derivations.
  • FIG. 17 shows an example of an LM parameter derivation process with 64 entries.
  • FIG. 18 shows a flowchart of an example method for video processing based on some implementations of the disclosed technology.
  • FIGS. 19A and 19B show flowcharts of example methods for video processing based on some implementations of the disclosed technology.
  • FIG. 20A and 20B show flowcharts of another example methods for video processing based on some implementations of the disclosed technology.
  • FIG. 21 shows a flowchart of another example method for video processing based on some implementations of the disclosed technology.
  • FIG. 22 shows a flowchart of an example method for video processing based on some implementations of the disclosed technology.
  • FIGS. 23A and 23B show flowcharts of example methods for video processing based on some implementations of the disclosed technology.
  • FIGS. 24A-24E show flowcharts of example methods for video processing based on some implementations of the disclosed technology.
  • FIGS. 26A and 26B show flowcharts of example methods for video processing based on some implementations of the disclosed technology.
  • FIGS. 28A-28C show flowcharts of example methods for video processing based on some implementations of the disclosed technology.
  • FIGS. 29A-29C show flowcharts of example methods for video processing based on some implementations of the disclosed technology.
  • FIGS. 30A and 30B are block diagrams of examples of hardware platforms for implementing a visual media decoding or a visual media encoding technique described in the present document.
  • FIGS. 31A and 31B show examples of LM parameter derivation process with four entries.
  • FIG. 31A shows an example when both above and left neighboring samples are available and
  • FIG. 31B shows an example when only above neighboring samples are available and top-right is not available.
  • FIG. 32 shows examples of neighboring samples to derive LIC parameters.
  • Video codecs typically include an electronic circuit or software that compresses or decompresses digital video, and are continually being improved to provide higher coding efficiency.
  • a video codec converts uncompressed video to a compressed format or vice versa.
  • the compressed format usually conforms to a standard video compression specification, e.g., the High Efficiency Video Coding (HEVC) standard (also known as H. 265 or MPEG-H Part 2) , the Versatile Video Coding (VVC) standard to be finalized, or other current and/or future video coding standards.
  • HEVC High Efficiency Video Coding
  • VVC Versatile Video Coding
  • Embodiments of the disclosed technology may be applied to existing video coding standards (e.g., HEVC, H. 265) and future standards to improve runtime performance.
  • Section headings are used in the present document to improve readability of the description and do not in any way limit the discussion or the embodiments (and/or implementations) to the respective sections only.
  • ⁇ and ⁇ in CCLM are derived from chroma samples at:
  • K may be 2, 4, 6 or 8.
  • which positions are selected may be signaled from the encoder to the decoder, such as in VPS/SPS/PPS/slice header/tile group header/tile/CTU/CU/PU.
  • the selected chroma samples are used to derive the parameters ⁇ and ⁇ with the least mean square method as shown in Eq (2) and Eq (3) .
  • N is set to be the number of the selected samples.
  • a pair of selected chroma samples are used to derive the parameters ⁇ and ⁇ with the two-point method.
  • how to select samples may depend on the availability of the neighboring blocks.
  • positions A, D, J and M are selected if both the left and the above neighboring blocks are available; position A and D are selected if only the left neighboring block is available; and position J and M are selected if only the above neighboring block is available.
  • Example 2 Sets of parameters in CCLM mode can be firstly derived and then combined to form the final linear model parameter used for coding one block.
  • ⁇ 1 and ⁇ 1 are derived from a group of chroma samples at specific positions denoted as Group 1
  • ⁇ 2 and ⁇ 2 are derived from a group of chroma samples at specific positions denoted as Group 2
  • ⁇ N and ⁇ N are derived from a group of chroma samples at specific positions denoted as Group N
  • the final ⁇ and ⁇ can be derived from ( ⁇ 1 , ⁇ 1 ) , ... ( ⁇ N , ⁇ N ) .
  • ⁇ is calculated as the average of ⁇ 1 , ... ⁇ N and ⁇ is calculated as the average of ⁇ 1 , ... ⁇ N .
  • ⁇ SignShift ( ⁇ 1 + ⁇ 2 , 1)
  • ⁇ SignShift ( ⁇ 1 + ⁇ 2 , 1) .
  • ⁇ Shift ( ⁇ 1 + ⁇ 2 , 1)
  • ⁇ Shift ( ⁇ 1 + ⁇ 2 , 1) .
  • ⁇ 1 SignShift ( ⁇ 1 , Sh 1 -Sh 2 )
  • ⁇ 1 SignShift ( ⁇ 1 , Sh 1 -Sh 2 )
  • the final precision is as ( ⁇ 2 , ⁇ 2 ) .
  • Group 1 Position A and I
  • Group 2 Position J and Q.
  • Group 1 Position A and D
  • Group 2 Position E and I, where there are two groups are used for mode LM-L.
  • Group 1 Position A and B
  • Group 2 Position C and D, where there are two groups are used for mode LM-L.
  • Group 1 Position J and K
  • Group 2 Position L and M, where there are two groups are used for mode LM-A.
  • Example 3 Suppose two chroma sample values denoted as C0 and C1, and their corresponding luma sample values denoted as L0 and L1 (L0 ⁇ L1) are inputs.
  • the two-point method can derive ⁇ and ⁇ with the input as
  • bit depths of luma samples and chroma samples are denoted BL and BC.
  • One or more simplifications for this implementation include:
  • ⁇ is output as 0 if L1 is equal to L0.
  • a certain intra prediction mode e.g., DM mode, DC or planar
  • CCLM mode e.g., DC or planar
  • log2 operation may be implemented by checking position of the most significant digit.
  • Example i or Example ii may be selected based on the value of L1-L0.
  • Example i is used if L1-L0 ⁇ T, otherwise Example ii is used.
  • T can be
  • Example i is used if otherwise Example ii is used.
  • Example i is used if otherwise Example ii is used.
  • V The size of the lookup table denoted as V is less than 2 P , where P is an integer number such as 5, 6, or 7.
  • W depends on BL, V and Z.
  • W also depends on the value of L1-L0.
  • Fig. 7 shows an example.
  • the top-left sample is at position (0, 0) .
  • iv. w1 and w2 may depend on the position (x, y)
  • ii. S0, S1, ...Sm are indices of selected groups which are used to calculate ⁇ and ⁇ .
  • samples (or down-sampled samples) located at above rows may be classified to one group and samples (or down-sampled samples) located at left columns of a block may be classified to another group.
  • samples are classified based on their locations or coordinates.
  • samples may be classified into two groups.
  • MaxL MaxLS0
  • MaxC MaxCS0
  • how to select the samples for each group may depend the availability of neighboring blocks.
  • MaxL /MaxC and MinL /MinC are directly found from position A and D when only the left neighboring block is available.
  • Example 6 It is proposed that whether and how to apply LM-L and LM-A mode may depend on the width (W) and height (H) of the current block.
  • a first context is used if the top-left neighboring block applies CCLM mode; and a second context is used if the top-left neighboring block does not apply CCLM mode.
  • the coding order of indications of LM and DM may be depend on the mode information of one or multiple neighboring blocks.
  • indications of the order may be signaled in in SPS/VPS/PPS/picture header/slice header/tile group header/LCUs/LCU/CUs.
  • samples may be located beyond the range of 2 ⁇ W above neighboring samples or 2 ⁇ H left neighboring samples as shown in FIG. 6.
  • LM mode With LM mode or LM-L mode, it may use a neighboring sample RecC [x-1, y+d] , where d is in the range of [T, S] .
  • T may be smaller than 0, and S may be larger than 2H-1.
  • LM mode or LM-A mode it may use a neighboring sample RecC [x+d, y] , where d is in the range of [T, S] .
  • T may be smaller than 0, and S may be larger than 2W-1.
  • Example 10 the chroma neighboring samples and their corresponding luma samples (may be down-sampled) are down-sampled before deriving the linear model parameters ⁇ and ⁇ as disclosed in Examples 1-7.
  • the width and height of the current chroma block is W and H.
  • whether and how to conduct down-sampling may depend on W and H.
  • the chroma neighboring samples and their corresponding luma samples are not down-sampled if W is equal to H.
  • the chroma neighboring samples and their corresponding luma samples (may be down-sampled) left to the current block are down-sampled if W ⁇ H.
  • the chroma neighboring samples and their corresponding luma samples (may be down-sampled) above to the current block are down-sampled if W > H.
  • FIG. 9 shows examples of samples to be picked up when position D and position M in FIG. 6 are used to derive ⁇ and ⁇ , and down-sampling performed when W>H.
  • S neighboring luma samples (maybe down-sampled) denoted as Lx1, Lx2, ..., LxS, and their corresponding chroma samples denoted as Cx1, Cx2, ...CxS are used to derive C0 and L0
  • T neighboring luma samples (maybe down-sampled) denoted as Ly1, Ly2, ..., LyT, and their corresponding chroma samples denoted as Cy1, Cy2, ...CyT are used to derive C1 and L1 as:
  • f0, f1, f2 and f3 are any functions.
  • f0 f1 f2 f3 are identical.
  • the set ⁇ x1, x2, ...xS ⁇ is identical to the set ⁇ y1, y2, ..., yT ⁇ .
  • the group of luma samples includes all neighboring samples used in VTM-3.0 to derive CCLM linear parameters.
  • the group of luma samples includes partial neighboring samples used in VTM-3.0 to derive CCLM linear parameters.
  • Ly1, Ly2, ..., LyS are chosen as the largest S luma samples of a group of luma samples.
  • the group of luma samples includes all neighboring samples used in VTM-3.0 to derive CCLM linear parameters.
  • the group of luma samples includes partial neighboring samples used in VTM-3.0 to derive CCLM linear parameters.
  • the group of luma samples includes four samples as shown in FIGS. 2-5.
  • Example 12 It is proposed to select other neighboring or downsampled neighboring samples based on the largest neighboring or downsampled neighboring sample in a given set of neighboring or downsampled neighboring samples.
  • samples are representing samples of one color component (e.g., luma color component) .
  • Samples used in CCLM/cross-color component process may be derived by corresponding coordinates of a second color component.
  • Example 13 In above examples, luma and chroma may be switched. Alternatively, luma color component may be replaced by the main color component (e.g., G) , and chroma color component may be replaced by dependent color component (e.g., B or R) .
  • main color component e.g., G
  • chroma color component may be replaced by dependent color component (e.g., B or R) .
  • Example 14 Selection of locations of chroma samples (and/or corresponding luma samples) may depend on the coded mode information.
  • FIG. 10 depicts the concepts of left column/above row/above-right row/below-left column relative to a block.
  • two samples may be selected.
  • top-right row is available, or when 1st top-right sample is available.
  • top-right row is available, or when 1st top-right sample is available.
  • two samples of left column may be selected
  • Example 15 In above examples, luma and chroma may be switched. Alternatively, luma color component may be replaced by the main color component (e.g., G) , and chroma color component may be replaced by dependent color component (e.g., B or R) .
  • main color component e.g., G
  • chroma color component may be replaced by dependent color component (e.g., B or R) .
  • W may be set to the width of current block.
  • W may be set to (L*width ofcurrent block) wherein L is an integer value.
  • L may be dependent on the availability of top-right block. Alternatively, L may depend on the availability of one top-left sample.
  • W may depend on the coded mode.
  • W may be set to the width of current block if the current block is coded as LM mode
  • W may be set to (L* width of current block) wherein L is an integer value if the current block is coded as LM-A mode.
  • L may be dependent on the availability of top-right block. Alternatively, L may depend on the availability of one top-left sample.
  • F W/P.
  • P is an integer.
  • P 2 i , where i is an integer such as 1 or 2.
  • S W/Q.
  • Q is an integer.
  • Q 2 j , where j is an integer such as 1 or 2.
  • F S/R.
  • R is an integer.
  • R 2 m , where m is an integer such as 1 or 2.
  • j. kMax and/or F and/or S and/or offset may depend on the prediction mode (such as LM, LM-A or LM-L) of the current block;
  • k. kMax and/or F and/or S and/or offset may depend on the width and/or height of the current block.
  • m. kMax and/or F and/or S and/or offset may depend on W.
  • H may be set to the height of current block.
  • H may be set to (height of current block + width of the current block) if the required above-right neighbouring blocks are available.
  • L may be dependent on the availability of below-left block. Alternatively, L may depend on the availability of one top-left sample.
  • P 2 i , where i is an integer such as 1 or 2.
  • Q 2 j , where j is an integer such as 1 or 2.
  • R 2 m , where m is an integer such as 1 or 2.
  • Z 2 n , where n is an integer such as 1 or 2.
  • j. kMax and/or F and/or S and/or offset may depend on the prediction mode (such as LM, LM-A or LM-L) of the current block;
  • k. kMax and/or F and/or S and/or offset may depend on the width and/or height of the current block.
  • l. kMax and/or F and/or S and/or offset may depend on H.
  • m. kMax and/or F and/or S and/or offset may depend on availability of neighbouring samples.
  • maxY/maxC and minY/minC are derived from two or four neighbouring chroma samples (and/or their corresponding luma samples which may be down-sampled) , and are then used to derive the linear model parameters with the 2-point approach.
  • Luma sample value of G0 [1] and G1 [1] are compared, if luma sample value of G0 [1] is larger than (or smaller than, or not larger than, or not smaller than) luma sample value of G1 [1] , then G0 and G1 are swapped.
  • the proposed method to derive the parameters used in CCLM may be used to derive the parameters used in LIC or other coding tools that relies on linear model.
  • the N neighboring samples may be defined as N/2 samples from above row; and N/2 samples from left column.
  • the picking up method may depend on the availability of the neighbouring blocks.
  • K1 neighbouring samples may be picked up from the left neighbouring samples and K2 neighbouring samples are picked up from the above neighbouring samples, if both above and left neighbouring samples are available.
  • K1 neighbouring samples may be picked up from the left neighbouring samples if only left neighbouring samples are available.
  • K1 4.
  • the above samples may be picked up with a first position offset value (denoted as F) and a step value (denoted as S) which may depend on the dimension of the current block and the availability of the neighbouring blocks.
  • F first position offset value
  • S step value
  • the left samples may be picked up with a first position offset value (denoted as F) and a step value (denoted as S) which may depend on the dimension of the current block and the availability of the neighboring blocks.
  • F first position offset value
  • S step value
  • the proposed method to derive the parameters used in CCLM may also be used to derive the parameters used in LIC, when the current block is affine-coded.
  • the above methods may be used to derive the parameters used in other coding tools that relies on linear model.
  • cross-component prediction mode is proposed wherein the chroma samples are predicted with corresponding reconstructed luma samples according to the prediction model, as shown in Eq. 12.
  • Pred C (x, y) denotes a prediction sample of chroma.
  • ⁇ and ⁇ are two model parameters.
  • Rec’L (x, y) is a down-sampled luma sample.
  • a six-tap filter is introduced for the luma down-sampled process for block A in FIG. 11, as shown in Eq. 13.
  • Rec′ L (x, y) (2 ⁇ Rec L (2x, 2y) +2 ⁇ Rec L (2x, 2y+1)
  • the above surrounding luma reference samples shaded in FIG. 11 are down-sampled with a 3-tap filter, as shown in Eq. 14.
  • the left surrounding luma reference samples are down-sampled according to Eq. 15. If the left or above samples are not available, a 2-tap filter defined in Eq. 16 and Eq. 17 will be used.
  • Rec′ L (x, y) (2 ⁇ Rec L (2x, 2y) +Rec L (2x-1, 2y) +Rec L (2x+1, 2y) ) >>2 (14)
  • Rec′ L (x, y) (2 ⁇ Rec L (2x, 2y) +Rec L (2x, 2y+1) +Rec L (2x, 2y-1) ) >>2 (15)
  • Rec′ L (x, y) (3 ⁇ Rec L (2x, 2y) +Rec L (2x, 2y+1) +2) >>2 (17)
  • the surrounding luma reference samples are down sampled to the equal size to the chroma reference samples.
  • the size is denoted as width and height.
  • a look-up table is applied to avoid the division operation when deriving ⁇ and ⁇ . The derivation methods is illustrated below.
  • each entry in the exemplary tables are designed to be with 16 bits, it can be easily transformed to a number with less bits (such as 8 bits or 12 bits) .
  • a table of entries with 8 bits can be attained as:
  • predModeIntra is equal to INTRA_LT_CCLM, the following applies:
  • variable arrays startPos [] and pickStep [] are derived as follows:
  • startPos [0] actualTopTemplateSampNum >> (2 + aboveIs4) ;
  • startPos [1] actualLeftTemplateSampNum >> (2 + leftIs4) ;
  • selectChromaPix [cnt] p [startPos [0] +cnt*pickStep [0] ] [-1] ;
  • minY is set equal to selectLumaPix [1]
  • minC is set equal to selectChromaPix [1]
  • maxY is set equal to selectLumaPix [0]
  • maxC is set equal to selectChromaPix [0]
  • minY is set equal to selectLumaPix [0]
  • minC is set equal to selectChromaPix [0]
  • variable arrays minGrpIdx and maxGrpIdx are initialized as:
  • the number of available neighbouring chroma samples on the top and top-right numTopSamp and the number of available neighbouring chroma samples on the left and left-below nLeftSamp are derived as follows:
  • predModeIntra is equal to INTRA_LT_CCLM, the following applies:
  • variable bCTUboundary is derived as follows:
  • variable cntN and array pickPosN [] with N being replaced by L and T are derived as follows:
  • variable startPosN is set equal to numSampN>> (2+numIs4N) .
  • variable pickStepN is set equal to Max (1, numSampN>> (1+numIs4N) ) .
  • cntN is set equal to (1+numIs4N) ⁇ 1
  • cntN is set equal to 0.
  • nTbH-1 is derived as follows:
  • nTbH-1 is derived as follows:
  • nTbW-1 is derived as follows:
  • nTbW-1 is derived as follows:
  • pDsY [0] [0] is derived as follows:
  • nTbH-1 is derived as follows:
  • nTbH-1 is derived as follows:
  • the variable y is set equal to pickPosL [idx] .
  • variable x is set equal to pickPosT [idx -cntL] .
  • variable pickStepN is set equal to Max (1, numSampN>> (1+numIs4N) ) .
  • cntN is set equal to Min (numSampN, (1+numIs4N) ⁇ 1)
  • cntN is set equal to 0.
  • nTbH-1 is derived as follows:
  • nTbH-1 is derived as follows:
  • nTbW-1 is derived as follows:
  • nTbW-1 is derived as follows:
  • nTbH-1 is derived as follows:
  • nTbH-1 is derived as follows:
  • the variable y is set equal to pickPosL [idx] .
  • variable x is set equal to pickPosT [idx -cntL] .

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