RU2810900C2 - Selection of neighbouring sample for internal prediction - Google Patents

Abstract

FIELD: video processing.

SUBSTANCE: invention relates to technologies, devices and systems for video processing. The result is achieved in that the video processing method includes determining the cross-component linear model (CCLM) prediction mode parameters based on chroma samples that are selected based on the available W top adjacent samples, where W is an integer, for conversion between the current video block of the video, which is a chrominance block, and the encoded representation of the video; and performing a conversion based on the determination.

EFFECT: increased efficiency of video processing.

14 cl, 31 dwg

Description

Cross reference to related applications

Field of technology to which the invention relates

This document relates to technologies, devices and systems for video processing.

State of the art

Despite advances in video compression, digital video still consumes the most bandwidth on the Internet and other digital communications networks. As the number of connected user devices capable of receiving and displaying video increases, the demand for bandwidth for digital video use is expected to continue to increase.

Disclosure of the invention

The present disclosure provides descriptions of devices, systems and methods related to digital video processing and, for example, the derivation of a simplified linear model for a cross-component linear model (CCLM) mode in video encoding. The described methods can be applied to both existing video coding standards (eg, High Efficiency Video Coding (HEVC)) and future video coding standards (eg, Versatile Video Coding (VVC)) or codecs.

In one exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises defining, for transforming between a current video block, which is a chrominance block, and an encoded video representation, cross-component linear model (CCLM) prediction mode parameters based on chrominance samples that are selected based on W available top neighboring samples, W being an integer ; and performing a conversion based on the definition.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: determining, for conversion between a current video block, which is a chrominance block, and an encoded video representation, cross-component linear model (CCLM) prediction mode parameters based on chroma samples that are selected based on H available left adjacent samples of the current video block; and performing a conversion based on the definition.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: determining, for conversion between a current video block, which is a chroma block, and a coded representation of the video, cross-component linear model (CCLM) parameters based on two or four chroma samples and/or corresponding luma samples; and performing a conversion based on the definition.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: selecting, to transform between a current video block, which is a chrominance block, and a coded representation of the video, chrominance samples based on a position rule, the chroma samples being used to obtain the parameters of a cross-component linear model (CCLM); and performing a conversion based on the determination in which the position rule specifies to select chroma samples that are located within the top row and/or left column of the current video block.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: determining, for conversion between a current video block, which is a chrominance block, and a coded video representation, positions at which luminance samples are downsampled, wherein the luminance samples after downsampling are used to determine the parameters of a cross-component linear model (CCLM) based on the chrominance samples and the downsampled luminance samples, wherein the downsampled luminance samples are at positions corresponding to positions of the chrominance samples that are used to obtain the CCLM parameters; and performing a conversion based on the definition.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: defining, for transforming between a current video block, which is a chrominance block, and a coded representation of the video, a method for deriving cross-component linear model (CCLM) parameters using chrominance samples and luminance samples based on an encoding condition associated with the current video block ; and performing a conversion based on the definition.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: determining, in order to transform between a current video block, which is a chroma block, and an encoded video representation, whether to obtain maximum values and/or minimum values of the luma component and the chroma component, which are used to obtain the parameters of the cross-component linear model (CCLM) based on the availability of the left adjacent block and the upper adjacent block of the current video block; and performing a conversion based on the definition.

In yet another exemplary aspect, the method described above is implemented in the form of processor-executable code and stored on a computer-readable medium.

In yet another exemplary aspect, there is provided a device configured to perform the method described above. The device may include a processor that is programmed to implement the method.

In yet another exemplary aspect, a video decoder device may implement the method described herein.

The above and other aspects and features of the disclosed technology are set forth in more detail in the description and claims with reference to the accompanying drawings.

Brief description of drawings

FIG. 1 shows an example of sample positions used to obtain linear model weights used for intercomponent prediction.

FIG. 2 shows an example of classifying adjacent samples into two groups.

FIG. 3A shows an example of a chrominance sample and its corresponding luma samples.

Fig. 3B shows an example of downward filtering for a cross-component linear model (CCLM) in a joint exploration model (JEM).

FIGS. 4A and 4B show examples of top neighbor only and left neighbor only samples used for prediction based on the linear model, respectively.

FIG. 5 shows an example of a straight line between minimum and maximum luminance values as a function of the corresponding chroma samples.

FIG. 6 shows an example of the current chroma block and its adjacent samples.

FIG. 7 shows an example of different parts of a chrominance block predicted by a linear model using only left neighbor samples (LM-L) and a linear model using only top neighbor samples (LM-A).

FIG. 8 shows an example of a top left adjacent block.

FIG. 9 shows an example of the samples used to obtain the linear model.

FIG. 10 shows an example of left and bottom-left columns and top and top-right rows relative to the current block.

FIG. 11 shows an example of the current block and its reference samples.

12 shows examples of two adjacent samples when both left and top adjacent reference samples are available.

FIG. 13 shows examples of two adjacent samples when only the top adjacent reference samples are available.

FIG. 14 shows examples of two adjacent samples when only the left adjacent reference samples are available.

FIG. 15 shows examples of four adjacent samples when both left and top adjacent reference samples are available.

FIG. 16 shows an example of lookup tables used in LM derivatives.

FIG. 17 shows an example of a process for obtaining an LM parameter with 64 entries.

18A and 18B show a flowchart of example methods for video processing based on some implementations of the disclosed technology.

FIGS. 19A and 19B show flowcharts of example video processing methods based on some implementations of the disclosed technology.

FIGS. 20A-20C show flowcharts of another example method for video processing based on some implementations of the disclosed technology.

FIGS. 21A and 21B are block diagrams of example hardware platforms for implementing visual media decoding or encoding technology described herein.

FIGS. 22A and 22B show examples of a four-entry LM parameter acquisition process. FIG. 22A shows an example when both the top and left neighbor samples are available, and FIG. 22B shows an example when only the top neighbor samples are available and the top-right is not available.

FIG. 23 shows examples of adjacent samples for obtaining LIC parameters.

Carrying out the invention

Due to the increasing need for higher resolution video, video encoding methods and technologies have been adopted in modern technologies. Video codecs typically include electronic circuitry or software that compresses or decompresses digital video and is constantly being improved to provide higher encoding efficiency. A video codec converts uncompressed video into a compressed format or vice versa. There are complex relationships between video quality, the amount of data used to represent the video (determined by the bit rate), the complexity of encoding and decoding algorithms, sensitivity to data loss and errors, ease of editing, random access, and end-to-end latency. The compressed format typically follows standard video compression specifications, such as 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 promising video coding standards.

Embodiments of the disclosed technology can be applied to existing video encoding standards (eg, HEVC, H.265) and emerging standards to improve processing performance. Section headings are used herein to enhance the readability of the description and in no way are the description or embodiments (and/or implementations) limited to their respective sections.

1. Options for implementing inter-component prediction

Intercomponent prediction is a form of chrominance-to-luminance prediction that has a well-balanced trade-off between complexity and increased compression efficiency.

1.1 Examples of cross-component linear model (CCLM)

In some embodiments, to reduce inter-component redundancy, JEM uses a inter-component linear model (CCLM) prediction mode (also referred to as LM), which predicts chroma samples based on reconstructed luminance samples of the same CU using a linear model as follows:

(1)

represents the predicted chrominance samples in the CU and represents the reconstructed luminance samples after downsampling the same CU for 4:2:0 or 4:2:2 color formats, where represents reconstructed luminance samples of the same CU for the 4:4:4 color format. The CCLM parameters α and β are obtained by minimizing regression errors between adjacent reconstructed luma and chrominance samples around the current block as follows:

(2) And (3)

represents the original (for 4:4:4 color format) or downsampled (for 4:2:0 or 4:2:2 color format) top and left adjacent reconstructed luma samples, or the original and left adjacent reconstructed luma samples, represents the top and left neighbors of the reconstructed chroma samples and the value equal to twice the minimum width and height of the current chrominance block.

In some embodiments, the above two equations are directly applied to the square-shaped encoding block. In other embodiments and for a non-square encoding block, adjacent samples of the longer boundary are first subsampled to obtain the same number of samples as the shorter boundary. Figure 1 shows the location of the left and top reconstructed samples and the current block sample used in CCLM mode.

In some embodiments, a regression error minimization calculation is performed as part of the decoding process, not in the same way as the encoder search operation, so the syntax is not used to convey the α and β values.

In some embodiments, the CCLM prediction mode also includes prediction between two chrominance components, eg, a Cr (red-difference) component is predicted from a Cb (cyan-difference) component. Instead of using the reconstructed sample signal in the residual domain, CCLM Cb-to-Cr prediction is applied. This is implemented by adding the weighted reduced Cb residue to the original Cr internal prediction to form the final Cr prediction:

(4)

is the reconstructed Cb sample of the residue at position (i, j).

In some embodiments, the scaling factor α may be obtained in a similar manner as in CCLM luma to chrominance prediction. The only difference is to add the regression cost relative to the default value of α to the error function, so that the resulting scaling factor is biased towards the default value of -0.5 as follows:

(5)

represents neighboring reconstructed Cb samples, represents the neighboring reconstructed Cr samples and λ is equal to .

In some CCLM embodiments, a luminance to chrominance prediction mode is added as one additional intra-chrominance prediction mode. On the encoder side, another RD cost check for the chrominance components is added to select the intra-chrominance prediction mode. When intra prediction modes other than the CCLM luma-to-chrominance prediction mode are used for CU chrominance components, CCLM Cb-to-Cr prediction is used to predict the Cr component.

1.2 Examples of multiple CCLM model

JEM uses two CCLM modes: single CCLM model mode and multiple CCLM model (MMLM) mode. As the name indicates, to predict chrominance samples, the single CCLM model mode uses one linear model from the luminance samples for the entire CU, and MMLM can use two models.

In MMLM, neighboring luma samples and neighboring chrominance samples of the current block are classified into two groups, each group is used as a training set to obtain a linear model (i.e., specific α and β are obtained for a specific group). Moreover, samples of the current luma block are also classified based on the same rule for classifying neighboring luma samples.

FIG. 2 shows an example of classifying adjacent samples into two groups. The threshold value is calculated as the average of neighboring reconstructed luminance samples. The adjacent sample with Rec′ _L [x,y] <= Threshold value is classified into group 1; while the neighboring sample with Rec′ _L [x,y] >Threshold value is classified into group 2.

(6)

1.3 Examples of downsampling filters in CCLM

In some embodiments, and to perform inter-component prediction for a 4:2:0 chroma format in which 4 luminance samples correspond to 1 chrominance sample, the reconstructed luminance block must be downsampled to match the size of the chrominance signal. The default downsampling filter used in CCLM mode is as follows:

(7)

Downsampling assumes "type 0" phase relationships, as shown in FIG. 3A for chroma sample positions relative to luma sample positions, eg, horizontal joint sampling and vertical interstitial sampling.

The default filter is the approximate 6-tap downsampling filter defined in (6) for both the single midship CCLM mode and the multiple midsection CCLM mode.

In some embodiments and for MMLM mode, the encoder may alternatively select one of four additional luminance downsampling filters to be applied for prediction to the CU, and send a filter index to indicate which one is used. The four selected downsampling filters for the MMLM mode, as shown in FIG. 3B, are as follows:

(8) (9) (10 (eleven)

1.4 Multidirectional LM (MDLM)

This implementation used offers multi-directional LM (MDLM). MDLM uses two additional CCLM modes: LM-A, in which the linear model parameters are obtained only from the top neighboring (or higher neighboring) samples, as shown in Fig. 4A, and LM-L, in which the linear model parameters are obtained only from based on the left adjacent samples, as shown in Fig. 4B.

1.5 Simplification of the intercomponent linear model

This used implementation proposes to replace the LMS algorithm of parameters α and β of the linear model by equation of a straight line, the so-called two-point method. The 2 points (luminance and chrominance pair) (A, B) are the minimum and maximum values within a set of adjacent luminance samples, as shown in Fig. 5

Here, the parameters α and β of the linear model are obtained according to the following equation:

In some embodiments, the division operation required in obtaining α should be omitted, and should be replaced by multiplications and shifts, as shown below:

a= 0;

iShift = 16;

int shift = (uiInternalBittDepth > 8)? uiInternalBitDepth - 9:0;

int add = shift? 1 << (shift - 1): 0;

int diff = (MaxLuma- MinLuma + add) >> shift;

if(diff>0)

{

int div = ((MaxChroma- MinChroma) * g_aiLMDivTableLow [diff - 1] + 32768) >> 16;

a = ((((MaxChroma- MinChroma) * g_aiLMDivTableHigh [diff - 1] + div + add) >> shift);

}

b = MinLuma[1] - ((a * MinLuma[0]) >> iShift);

Here S is set equal to iShift, α is set equal to a and β is set equal to b. Additionally, g_aiLMDivTableLow and g_aiLMDivTablehigh are two tables each with 512 entries, in which each entry stores a 16-bit integer.

To obtain the chroma predictor, as far as the current VTM implementation is concerned, the multiplication is replaced by an integer operation as follows:

This implementation is also simpler than the current VTM implementation since shift S always has the same value.

1.6 CCLM to VVC examples

CCLM as in JEM is accepted in VTM-2.0, but MM-CCLM in JEM is not accepted in VTM-2.0. MDLM and simplified CCLM were adopted in VTM-3.0.

1.7 Examples of local backlight compensation in JEM

Local backlight compensation (LIC) is based on a linear model for illumination variations using a scaling factor a and an offset b. And is used or disabled adaptively for each encoded coding unit (CU) in outer coding mode.

When LIC is applied to a CU, the least square error method is used to obtain the a and b parameters using the current CU's neighboring samples and their corresponding reference samples. More specifically, as shown in FIG. 23, subsampled adjacent samples (2:1 subsampling) of the CU and corresponding pixels (identified by the motion information of the current CU or sub-CU) in the reference image are used. IC parameters are obtained and applied for each prediction direction separately.

When a CU is encoded using 2NX2N merging mode, the LIC flag is copied from neighboring blocks similar to copying motion information in merging mode; otherwise, the LIC flag is signaled to the CU to indicate whether LIC is applied or not.

When using LIC on an image, an additional RD level CU check is required to determine whether LIC is applied or not on the CU. When LIC is applied to CU, sum with mean absolute difference removed (MR-SAD) and sum with mean absolute absolute difference removed (MR-SATD) are used instead of SAD and SATD for integer pixel motion search and fractional pixel motion search , respectively.

To reduce coding complexity, JEM uses the following coding scheme: LIC is disabled for the entire image when there is no obvious illumination change between the current image and its reference images. To identify this situation, the encoder calculates histograms of the current image and each reference image of the current image. If the histogram difference between the current image and each reference image of the current image is less than a specified threshold, LIC is disabled for the current image; otherwise, LIC is enabled for the current image.

2 Examples of shortcomings in existing implementations

In JEM, current implementations introduce a point-to-point method to replace the LMS approach of the LM mode. Although the new method reduces the number of additions and multiplications in CCLM, it still requires solving the following technical problems:

1) Finding minimum and maximum brightness values that are not single-instruction friendly requires software multiple data comparison (SIMD).

2) two lookup tables with 1024 entries storing 16-bit numbers are introduced, requiring 2K ROM memory, which is not desirable in hardware.

3 Exemplary methods for inter-component prediction in video encoding

Embodiments of the present invention solve technical problems of existing implementations, thereby providing video encoding with higher encoding efficiency and lower computational complexity. Simplified linear models for inter-component prediction based on the disclosed technology can improve both current and future video coding standards, which are illustrated in the following examples described for various implementations. The examples of technology disclosed below explain general concepts and are not intended to be interpreted as limitations. In the example, unless explicitly stated otherwise, various features described in these examples may be combined.

In the following examples and methods, the term "LM method" includes, but is not limited to, LM mode in JEM or VTM and MMLM mode in JEM, left-LM mode, which uses only left adjacent samples to obtain a linear model, top-LM mode , which uses only the top neighbor samples to obtain a linear model, or other kinds of methods that use the reconstructed luma samples to obtain chrominance prediction blocks. All LM modes that are neither LM-L nor LM-A are called normal LM modes.

In the following examples and methods, Shift(x, s) is defined as and Signshift(x, s) is defined as

Here off is an integer such as 0 or 2 ^S-1 .

The height and width of the chrominance current block are denoted by H and W, respectively.

FIG. 6 shows an example of adjacent samples of the current chroma block. Let's say the coordinate of the top left sample of the current chrominance block will be denoted as (x, y). Adjacent chrominance samples (as shown in Fig. 6) are then designated as:

A: top left selection: [x-1, y],

B: top middle sample left: [x-1, y + H/2-1],

C: bottom middle sample left: [x-1, y + H/2],

D: bottom left selection: [x-1, y + H-1],

E: extended bottom top left selection: [x-1, y + H],

F: extended lower upper middle left sample: [x-1, y+ H + H/2-1],

G: extended bottom middle sample left: [x-1, y + H + H/2],

I: extended bottom left selection: [x-1, y + H + H-1],

J: left sample above: [x, y-1],

K: left middle sample above: [x + W/2-1, y-1],

L: right middle sample above: [x + W/2, y-1],

M: Right sample above: [x+W-1, y-1],

N: extended above left sample above: [x + W, y-1],

O: extended above average sample above: [x + W + W/2-1, y-1],

P: extended above right middle sample above: [x + W + W/2, y-1] and

Q: extended above right sample above: [x + W + W-1, y-1].

Example 1. The parameters α and β in LM methods are obtained from chromaticity samples at two or more specific positions.

a. The acquisition also depends on the corresponding downsampled luma samples of the selected chrominance samples. Alternatively, the acquisition also depends on the corresponding luminance samples of the selected chroma samples, such as a 4:4:4 color format.

b. For example, the parameters α and β in CCLM are obtained from chroma samples at 2 ^S (e.g. S = 2 or 3) positions, such as:

i. Position {A, D, J, M};

ii. Position {A, B, C, D, J, K, L, M};

iii. Position {A, I, J, Q};

iv. Position {A, B, D, I, J, K, M, Q};

v. Position {A, B, D, F, J, K, M, O};

vi. Position {A, B, F, I, J, K, O, Q};

vii. Position {A, C, E, I, J, L, N, Q};

viii. Position {A, C, G, I, J, L, P, Q};

ix. Position {A, C, E, G, J, L, N, P};

x. Position {A, B, C, D};

xi. Position {A, B, D, I};

xii. Position {A, B, D, F};

xii. Position {A, C, E, I};

xiv. Position {A, C, G, I};

xv. Position {A, C, E, G};

xvi. Position {J, K, L, M};

xvii. Position {J, K, M, Q};

xviii. Position {J, K, M, O};

xix. Position {J, K, O, Q};

xx. Position {J, L, N, Q};

xxi. Position {J, L, P, Q};

xxii. Position {J, L, N, P};

xxiii. Position {A, B, C, E, E, F, G, I};

xxiv. Position {J, K, L, M, N, O, P, Q};

With. For example, the parameters α and β in CCLM are obtained from the chrominance samples on:

i. Any combination between {A, B, C, D, E, F, G, I} and {J, K, L, M, N, O, P, Q} such as

(a) position A and J;

(b) position B and K;

(c) position C and L;

(d) position D and M;

(e) position E and N;

(f) position of F and O;

(g) position G and P;

(h) position I and Q;

ii. Any two different positions extracted from {A, B, C, D, E, F, G}

(a) position A and B;

(b) position A and C;

(c) position A and D;

(d) position A and E;

(e) position A and F;

(f) position A and G;

(g) position A and I;

(h) position D and B;

(i) position D and C;

(j) position E and B;

(k) position E and C;

(l) position I and B;

(m) position I and C;

(n) position I and D;

(o) position I and E;

(p) position I and F;

(q) position I and G;

iii. Any two different positions drawn from {J, K, L, M, N, O, P, Q}

(a) position of J and K;

(b) position J and L;

(c) position J and M;

(d) position J and N;

(e) J and O position;

(f) J and P position;

(g) J and Q position;

(h) position of M and K;

(i) position M and L;

(j) N and K position;

(k) N and L position;

(l) position of Q and K;

(m) position of Q and L;

(n) Q and M position;

(o) Q and N position;

(p) position of Q and O;

(q) position of Q and P;

(r) position of Q and Q;

iv. In one example, if two selected positions have the same brightness value, more positions may be further tested.

d. For example, not all available chrominance samples are searched to find the minimum and maximum luminance values to obtain the α and β parameters in CCLM using a two-point method.

i. One chroma sample of the K chroma samples (and their corresponding downsampled luma samples) is included in the search set. K can be 2, 4, 6 or 8.

(a) For example, if Rec[x,y] is the top neighbor sample, then it is included in the search set only if x%K == 0. If Rec[x,y] is the left neighbor sample, then it is included in search set only if y%K == 0.

ii. Only chroma samples at specific positions, such as those defined in 1.a.i ~ 1.a.xxiv, are included in the search set.

e. For LM-L mode, all selected samples must be left adjacent samples.

f. For LM-A mode, all selected samples must be top adjacent samples.

g. The selected positions can be fixed, or they can be adaptive.

i. In one example, which positions are selected may depend on the width and height of the current chroma block;

ii. In one example, the mapping positions may be signaled from the encoder to the decoder, for example, in VPS/SPS/PPS/segment header/tile group header/tile/CTU/CU/PU.

h. The selected chrominance samples are used to obtain the parameters α and β by least squares, as shown in equation (2) and equation (3). In Equation (2) and Equation (3), N is the number of samples selected.

i. A pair of selected chrominance samples are used to obtain the parameters α and β in a two-point manner.

j. In one example, how to select samples may depend on the availability of neighboring blocks.

i. For example, positions A, D, J, and M are selected if both left and top adjacent blocks are available; positions A and D are selected if only the left adjacent block is available; and positions J and M are selected if only the top adjacent block is available.

Example 2 Parameter sets can be obtained first in CCLM mode and then combined to form the parameter of the final linear model used to encode a single block. Suppose that α ₁ and β ₁ are obtained from a group of chrominance samples at specific positions, denoted group 1, α ₂ and β ₂ , obtained from a group of chrominance samples at specific positions, denoted group 2, ..., α _n and β _n obtained from a group of chromaticity samples at specific positions, denoted as group N, then the final α and β can be obtained from (α ₁ , β ₁ ), ... (α _n , β _n ).

A. In one example, α is calculated as the average of α ₁ , ... α _n and β is calculated as the average of β ₁ , ... β _N .

i. In one example, α = SignsShift (α ₁ + α ₂ , 1), β = SignShift(β ₁ + β ₂ , 1).

ii. In one example, α=Shift(α ₁ + α ₂ , 1), β=Shift(β ₁ + β ₂ , 1).

iii. If (α ₁ , β ₁ ) and (α ₂ , β ₂ ) have different precision, for example, to obtain a chrominance prediction CP from its corresponding downsampled luminance sample LR is calculated as

with (α ₁ , β ₁ ), but

since (α ₂ , β ₂ ) Sh ₁ is not equal to Sh ₂ , then the parameters must be shifted before combining. Assuming Sh ₁ > Sh ₂ , then before merging the parameters should be shifted as:

- . The final precision is then (α ₂ , β ₂ ).

- . The final precision is then (α ₂ , β ₂ ).

(With) .Then the final precision is (α ₁ , β ₁ )

b.Some examples of positions in group 1 and group 2:

i. Group 1: Position A and D, Group 2: Position J and M.

ii. Group 1: Position A and I, Group 2: Position J and Q.

iii. Group 1: Position A and D, Group 2: Position E and I, where there are two groups used for LM-L mode.

iv. Group 1: J and M position, group 2: N and Q position, where there are two groups used for LM-A mode.

v. Group 1: Position A and B, Group 2: Position C and D, where there are two groups used for LM-L mode.

vi. Group 1: J and K position, group 2: L and M position, where there are two groups used for LM-A mode.

Example 3 Suppose that two chrominance sample values, denoted as C0 and C1, and their corresponding luma sample values, denoted as L0 and L1 (L0 < L1), are the input values. By performing the point-to-point method, one can obtain α and β with input values as

The bit depths of luma samples and chrominance samples are designated BL and BC. One or more simplifications for this implementation include:

A. α is output as 0 if L1 is equal to L0. Alternatively, when L1 is equal to L0, instead of using a particular intra prediction mode (eg, DM mode, DC or planar) is used using CCLM mode to obtain the prediction block.

b. The split operation is replaced by other operations without a lookup table. log2 operation can be implemented by checking the position of the most significant digit.

i. or

ii. or

iii. Example i or example ii may be selected based on the value of L1-L0.

(a) For example, example i is used if L1-L0 < T is used, otherwise example ii is used. For example, T could be

(b) For example, example i is used if example ii is used otherwise.

(c) For example, example i is used if example ii is used otherwise.

With. The partitioning operation is replaced by a single lookup table, denoted M[k].

i. The size of the lookup table, denoted V, is less than 2 ^p , in which p is an integer such as 5, 6, or 7.

ii. Each lookup table entry stores an F-bit integer, such as F = 8 or 16.

- In one example, M[k-Z] = ((1 << S) + Off)/k, in which S is an integer defining the precision, e.g. S = F. Off is the offset, e.g. Off = (k + Z ) >> 1. Z specifies the initial value of the table, for example Z = 1 or Z = 8 or Z = 32. A valid table query key k must satisfy k > = Z.

iii. k=Shift(L1-L0, W) is used as the key to query the lookup table.

(a) In one example, W depends on BL, V and Z.

(b) In one example, W also depends on the value of L1-L0.

iv. If k is not a valid key for the lookup table query (k-Z <0 or k-Z> = V), α is output as 0.

v. For example,

or

vi. To obtain a CP chrominance prediction from a corresponding (e.g., 4:2:0 downsampled) LR luminance sample, is calculated as

or

vii. Sh may be a fixed number, or may depend on the values of C0, C1, L0, L1 used to calculate α and β.

(a) Sh may depend on BL, BC, V, S and D.

(b) D may depend on Sh.

viii. The size of the lookup table, denoted by V, is 2 ^P , in which P is an integer such as 5, 6, 7, or 8. Alternatively, V is set to 2 ^P - M (for example, M is 0).

ix. Suppose α = P/Q (for example, Q = L1-L0, P = C1-C0 or they are obtained in other ways), then α is calculated with a lookup table in the form α = Shift(P×M[k−Z], D ) or α = SignShift(P×M[k−Z], D), in which k is the key (index) to query the entry in the lookup table.

(a) In one example, k is obtained from Q with the function: k = f(Q).

(b) In one example, k is obtained from Q and P, with the function: k = f(Q, P).

(c) In one example, k is valid in the specific range [kMin, kMax]. For example, kMin = Z and kMax = V + Z.

(d) in one example k = Shift(Q, W),

A. W may depend on BL, V and Z.

b. W may depend on the value of Q.

With. In one example, when k is calculated as Shift(Q, W), then α is calculated with a lookup table of the form

α = (Shift(P×M[k−Z], D)) << W or

α = (SignShift(P×M[k−Z], D)) << W

(e) In one example, k is obtained differently with different values of Q.

A. For example, k = Q for Q <= kMax and k = Shift (Q, W) for Q > kMax. For example, W is chosen to be the smallest positive integer that ensures Shift(Q, W) does not exceed kMax.

b. For example, k = Min (kMax, Q).

With. For example, k = Max(kMin, Min(kMax, Q)).

(f) In one example, when Q < 0, -Q is used to replace Q in the calculation. Then -α is output.

(g) In one example, when Q is 0, then α is set to a default value such as 0 or 1.

(h) In one example, when Q is 2 ^E E > = 0, then α = Shift(P, E) or α = SignShift(P, E).

d. All operations to obtain LM parameters must be within K bits, K can be 8, 10, 12, 16, 24 or 32.

i. If a transient variable can exceed the range represented by the limited bit, then a constraint or right shift must be performed to be within the limited bits.

Example 4 One of a single chroma block may use multiple linear models, and the choice of multiple linear model depends on the position of the chroma samples within the chroma block.

A. In one example, LM-L and LM-A mode can be combined in one chroma block.

b. In one example, some samples are predicted by the LM-L mode and other samples are predicted by the LM-A mode.

i. FIG. 7 shows an example. Let's assume that the top left sample is at position (0,0). Samples at position (x, y) with x>y (or x>=y) are predicted by LM-A and other samples are predicted by LM-L.

With. Suppose the prediction LM-L and LM-A for the sample at position (x, y) are denoted by P1(x, y) and P2(x, y), respectively, then the final prediction P(x, y) is calculated as a weighted sum P1 (x, y) and P2 (x, y).

i. P (x, y) = w1 * P1 (x, y) + w2 * P2 (x, y)

(a) w1 + w2 = 1.

ii. P (x, y) = (w1 * P1 (x, y) + w2 * P2 (x, y) + Offset) >> shift in which offset can be 0 or 1 << (shift-1) and Shift is an integer such as 1, 2, 3....

(a) w1 + w2 = 1 << shift.

iii. P (x, y) = (w1 * P1 (x, y) + ((1 << shift) -w1) * P2 (x, y) + Offset) >> shift in which the offset can be 0 or 1 < < (shift-1) and shift is an integer such as 1, 2, 3....

iv. w1 and w2 can depend on position (x, y)

(a) For example, w1> w2 (for example, w1 = 3, w2 = 1), if x <y,

(b) For example, w1 <w2 (for example, w1 = 1, w2 = 3), if x> y,

(c) For example, w1 = w2 (for example, w1 = 2, w2 = 2), if x == y,

(d) For example, w1 - w2 increases if y-x increases when x < y,

(e) For example, w2 - w1 increases if x-y increases when x>y.

Example 5: It is proposed that the adjacent samples (including the chrominance samples and their corresponding luma samples, which can be downsampled) are divided into N groups. The maximum luma value and the minimum luma value for the kth group (with k = 0, 1, ..., N-1) are denoted as MaxL _k and MinL _k and their corresponding chromaticity values are denoted as MaxC _k and MinC _k , respectively.

A. In one example, MaxL is calculated as MaxL=f1(MaxL _S0 , MaxL _S1 , ..., MaxL _Sm ); MaxC is calculated as MaxC=f2(MaxC _S0 , MaxC _S1 ,…MaxC _Sm ); MinL is calculated as MinL=f3(MinL _S0 , MinL _S1 ,…MinL _Sm ). MinC is calculated as MinC=f3(MinC _S0 , MinC _S1 , …, MinC _Sm ). f1, f2, f3 and f4 are functions. By performing the point-to-point method, α and β are obtained with input as:

i. In one example, f1, f2, f3, and f4 all represent an averaging function.

ii. S0, S1, ... Sm are the indices of the selected groups, which are used to calculate α and β.

(1) For example, all groups are used, for example, S0 = 0, S1 = 1, ... Sm = N-1.

(2) For example, two groups are used, for example, m = 1, S0=0, S1 = N-1.

(3) For example, not all groups are used, for example, m <N-1, S0 = 0, S1 = 2, S3 = 4, ...

b. In one example, samples (or downsampled samples) located in the top rows can be classified into one group, and samples (or downsampled samples) located in the left column of a block can be classified into another group.

c. In one example, samples (or downsampled samples) are classified based on their locations or coordinates.

i. For examples, samples can be classified into two groups.

(1) For a sample with coordinate (x, y) located on the top row, classify into group S0 if x% P = Q in which P and Q are integers, e.g. P = 2, Q = 1, P = 2, Q = 0 or P = 4, Q = 0; Otherwise, classified into group S1.

(2) For a sample with coordinate (x, y) located in the left column, classified into group S0 if y% P = Q in which P and Q are integers, e.g. P = 2, Q = 1, P = 2, Q = 0 or P = 4, Q = 0; Otherwise, classified into group S1.

(3) Only samples in one group, such as S0, are used to search for MaxC and MaxL. For example, MaxL= MaxLS0 and MaxC= MaxCS0.

d. In one example, only partial ones from adjacent samples (or downsampled samples) are used to split N into groups.

e. The number of groups (e.g. N) and/or indices of selected groups and/or functions (f1/f2/f3/f4) can be predefined or signaled in SPS/VPS/PPS/Image Header/Segment Header/Tile Group Header/LCUs /LCU/CUs.

f. In one example, how to select samples for each group may depend on the availability of neighboring blocks.

i. For example, MaxL ₀ /MaxC ₀ and MinL ₀ /MinC ₀ are determined from position A and D; MaxL ₁ /MaxC ₁ and MinL ₁ /MinC ₁ are determined from the position of J and M, then MaxL= (MaxL ₀ + MaxL ₁ )/ 2, MaxC= (MaxC ₀ + MaxC ₁ )/ 2, MinL= (MinL ₀ + MinL ₁ )/ 2, MinC= (MinC ₀ + MinC ₁ )/ 2, when both left and top adjacent blocks are available.

ii. For example, MaxL/MaxC and MinL/MinC are directly determined from position A and D when only the left adjacent block is available.

(1) Alternatively, α and β are set to their default values if the upper adjacent block is unavailable. For example, α = 0 and β = 1 << (bitDepth -1), in which bitDepth is the bit depth of the chroma samples.

iii. For example, MaxL/MaxC and MinL/MinC are directly determined from position J and M when only the top adjacent block is available.

(1) Alternatively, α and β are set to their default values if the left adjacent block is unavailable. For example, α = 0 and β = 1 << (bitDepth -1), in which bitDepth is the bit depth of the chroma samples.

g. In one example, how to select selections for each group may depend on the width and height of the block.

h. In one example, how to select samples for each group may depend on the values of the samples.

i, in one example, two samples with the largest brightness value and the minimum brightness value for the first group are selected. And all other samples are in the second group.

Example 6. It is suggested that and how to apply LM-L and LM-A mode may depend on the width (W) and height (H) of the current block.

(a) For example, LM-L cannot be applied if W> K × H. e.g. K = 2.

(b) For example, LM-A cannot be applied if H > K × W, e.g. K = 2.

(c) If one of LM-L and LM-A cannot be used, the flag to indicate the use of LM-L or LM-A should not be signaled.

Example 7: A flag is signaled to indicate whether CCLM mode is applied. The context used in the arithmetic encoding of the flag code may depend on whether the upper left adjacent block, as shown in FIG. 8, applies CCLM mode or not.

(a) In one example, the first context is used if the top left adjacent block uses CCLM mode; and the second context is used if the top left adjacent block does not apply CCLM mode.

(b) In one example, if the top left adjacent block is not available, then it is treated as not applying CCLM mode.

(c) In one example, if the top left adjacent block is unavailable, then it is considered to be in CCLM mode.

(d) In one example, if the top left adjacent block is not intra-coded, then it is considered not to be in CCLM mode.

(e) In one example, if the top left adjacent block is not intra-coded, then it is considered to be in CCLM mode.

Example.8. DM and LM mode instructions or codewords may be encoded in different orders from sequence to sequence/picture to pic/tile to tile/block to block.

(a) The order of encoding the DM and LM instructions (e.g., first, the LM mode code, if not, then the DM mode code; or, first, the code, whether DM mode, if not, then the LM mode code) may be dependent on the mode information of one or more neighboring blocks.

(b) In one example, when the top left block of the current block is available and encoded using the LM mode, the LM mode indication is encoded first.

(c) Alternatively, when the top left block of the current block is available and DM mode encoded, the DM mode indication is encoded first.

(d) Alternatively, when the upper left block of the current block is available and encoded in a non-LM mode (eg, DM mode or other intra prediction modes other than LM), then the DM mode indication is encoded first.

(e) In one example, order indications may be signaled in the SPS/VPS/PPS/picture header/segment header/tile group header/LCUs/LCUs/CUs.

Example 9 In the above examples, the samples (or downsampled samples) may be located outside the range of the 2×W top adjacent samples or the 2×H left adjacent samples, as shown in FIG. 6.

(a) By LM mode or LM-L mode, the adjacent sample RecC[x-1, y+d] in which d is in the range [T, S] can be used. T may be less than 0 and S may be greater than 2H-1. For example, T = -4 and S = 3H. In another example, T = 0, S = max (2H, W + H). In another example, T = 0 and S = 4H.

(b) By LM mode or LM-A mode, the adjacent sample RecC[x+d, y] in which d is in the range [T, S] can be used. T may be less than 0 and S may be greater than 2 W-1. For example, T = -4 and S = 3W. In another example, T = 0, S = max (2W, W + H). In another example, T = 0 and S = 4W.

Example 10 In one example, adjacent chroma samples and their corresponding luma samples (which may be downsampled) are downsampled to obtain the linear model parameters α and β as disclosed in Examples 1-7. Let's assume that the width and height of the current chrominance block are W and H.

(a) In one example, whether and how to perform the downsampling process may depend on W and H.

(b) In one example, the number of neighboring samples used to obtain parameters to the left of the current block and the number of neighboring samples used to obtain parameters above the current block must be the same after the downsampling process.

(c) In one example, adjacent chrominance samples and their corresponding luma samples (which may be downsampled) are not downsampled if W is equal to H.

(d) In one example, adjacent chrominance samples and their corresponding luma samples (downsampled) to the left of the current block are downsampled if W < H.

(i) In one example, one chroma sample in each H/W chroma sample is selected to be used to obtain α and β. Other chroma samples are discarded. For example, suppose R[0, 0] represents the top left sample of the current block, then R[-1, k * H/W], K from 0 to W-1, are selected to be used to obtain α and β.

(e) In one example, adjacent chrominance samples and their corresponding luma samples (which may be downsampled) above the current block are downsampled if W > H.

(ii) In one example, one chroma sample in each of the W/H chroma samples is selected to obtain α and β. Other chroma samples are discarded. For example, suppose R[0, 0] represents the top left sample of the current block, then R[K * W/H, -1], K from 0 to H-1 are selected to obtain α and β.

(ii) FIG. 9 shows examples of samples to be selected when position D and position M in FIG. 6 are used to obtain α and β, and downsampling is performed when W>H.

Example 11 Neighboring originally reconstructed/downsampled samples and/or initially reconstructed/downsampled samples can be further refined before being used in a linear model prediction process or an intercomponent color prediction process.

(a) "to be specified" may refer to filtering processing.

(b) "to be specified" may refer to any non-linear processing.

(c) It is proposed that several adjacent samples (including the chrominance samples and their corresponding luma samples, which may be downsampled) are selected to calculate C1, C0, L1 and L0 to obtain α and β, e.g. α = (C1 -C0)/(L1-L0) and β = C0 - αL0.

(d) In one example S, adjacent luminance samples (may be downsampled), denoted Lx1, Lx2, ..., LxS, and their corresponding chrominance samples, denoted Cx1, Cx2, ... CxS, are used to obtain C0 both L0 and T adjacent luminance samples (may be downsampled), denoted Ly1, Ly2, ..., LyT and their corresponding chrominance samples, denoted Cy1, Cy2, ... CyT are used to obtain C1 and L1 as :

(i) C0=f0(Cx1, Cx2, … CxS), L0=f1(Lx1, Lx2, … LxS), C1=f2(Cy1, Cy2, … CyT), L1=f4(Ly1, Ly2, … LyT) . f0, f1, f2 and f3 are any functions.

(ii) In one example, f0 is identical to f1.

(iii) In one example, f2 is identical to f3.

(iv) In one example f0 f1 f2 f3 are identical.

1. For example, all functions are averaging functions.

(v) In one example, S is equal to T.

1. In one example, the set {x1, x2, ... xS} is identical to the set {y1, y2, ..., yT}.

(vi) In one example, Lx1, Lx2, ..., LxS are selected as the smallest luminance samples of a group of luminance samples.

1. For example, a group of luminance samples includes all neighboring samples used in VTM-3.0 to obtain linear CCLM parameters.

2. For example, a group of luminance samples includes partial neighboring samples used in VTM-3.0 to obtain linear CCLM parameters.

A. For example, the luminance sample group includes four samples, as shown in FIGS. 2-5.

(vii) In one example, Ly1, Ly2, ..., LyS are selected as the largest luminance samples S of a group of luminance samples.

1. For example, a group of luminance samples includes all neighboring samples used in VTM-3.0 to obtain linear CCLM parameters.

2. For example, a group of luminance samples includes partial neighboring samples used in VTM-3.0 to obtain linear CCLM parameters.

a. For example, the luminance sample group includes four samples, as shown in FIGS. 2-5.

Example 12: It is proposed to select other adjacent or adjacent downsampled samples based on the largest adjacent or adjacent downsampled sample in a given set of adjacent or adjacent downsampled samples.

(a) In one example, the largest neighbor or downsampled neighbor located at position (x0, y0) is denoted. Samples in the region (x0-d1, y0), (x0, y0-d2), (x0 + d3, y0), (x0, y0 + d4) can then be used to select other samples. The number of integers {d1, d2, d3, d4} can depend on the position (x0, y0). For example, if (x0, y0) is to the left of the current block, then d1 = d3 = 1 and d2 = d4 = 0. If (x0, y0) is above the current block, then d1 = d3 = 0 and d2 = d4 = 1 .

(b) In one example, denote the smallest neighbor or adjacent downsampled sample located at position (x1, y1). Samples in the region (x1-d1, y1), (x1, y1-d2), (x1 + d3, y1), (x1, y1 + d4) can then be used to select other samples. Integers {d1, d2, d3, d4} can depend on the position (x1, y1). For example, if (x1, y1) is to the left of the current block, then d1 = d3 = 1 and d2 = d4 = 0. If (x1, y1) is above the current block, then d1 = d3 = 0 and d2 = d4 = 1 .

(c) In one example, the top samples represent samples of one color component (eg, the luminance color component). The samples used in the CCLM/intercomponent color process can be obtained by the corresponding coordinates of the second color component.

(d) A similar method can be used to obtain the smallest samples.

Example 13: In the above examples, brightness and chroma can be switched. Alternatively, the luminance color component may be replaced by a primary color component (eg, G) and the chrominance color component may be replaced by a dependent color component (eg, B or R).

Example 14 The selection of chrominance sample locations (and/or corresponding luminance samples) may depend on the encoded mode information.

(a) Alternatively, it may also depend on the availability of adjacent samples, such as the left column or top row or the top right row or bottom left column. 10 depicts the concepts of left column/top row/top right row/bottom left column with respect to a block.

(b) Alternatively, it may also depend on the availability of samples located at specific positions, such as the 1st top right sample and/or the 1st bottom left sample.

(c) Alternatively, it may also depend on the block dimensions.

(i) Alternatively, it may also depend on the relationship between the width and height of the current chrominance (and/or luminance) block.

(ii) Alternatively, it may also depend on whether the width and/or height of K is equal (eg k = 2).

(d) In one example, when the current mode is the normal LM mode, the following methods for selecting chrominance samples (and/or luminance samples with or without downsampling) can be applied:

(i) If both the left column and the top row are available, then the two left column samples and the top two rows can be selected. They can be located at (assuming the top left coordinate of the current block is (x, y)):

1. (x-1, y), (x, y-1), (x-1, y+H-1) and (x + W-1, y-1)

2. (x-1, y), (x, y-1), (x-1, y + H - H/W -1) and (x + W-1, y-1). For example, when H is greater than W.

3. (x-1, y), (x, y-1), (x-1, y + H -1) and (x + W - W/H-1, y-1). For example, when H is less than W.

4. (x-1, y), (x, y-1), (x-1, y + H – max(1, H/W)) and (x + W- max(1, W/H) , y-1).

(ii) If only the top row is available, then only the samples from the top row are selected.

1. For example, four samples of the top row may be selected.

2. For example, two samples may be selected.

3. How to select samples may depend on the width/height. For example, four samples are selected when W > 2 and two samples are selected when W = 2.

4. Selected samples can be located at (assume the top left coordinate of the current block is (x, y)):

a. (x, y-1), (x + W/4, y-1), (x + 2*W/4, y-1), (x + 3*W/4, y – 1)

b. (x, y-1), (x + W/4, y-1), (x + 3*W/4, y – 1), (x + W-1, y -1)

c. (x, y-1), (x + (2W)/4, y-1), (x + 2*(2W)/4, y-1), (x + 3*(2W)/4, y - 1).

For example, when the top right row is available, or when the 1st top right selection is available.

d. (x, y-1), (x + (2W)/4, y-1), (x + 3*(2W)/4, y – 1), (x + (2W)-1, y -1 )

For example, when the top right row is available or when the 1st top right selection is available.

(iii) If only the left column is available, only the samples from the left column are selected.

1. For example, four samples of the left column can be selected;

2. For example, two samples of the left column may be selected;

3. How to choose samples may depend on the width/height. For example, four samples are selected when H > 2 and two samples when H = 2.

4. Selected selections can be located on:

a. (x-1, y), (x -1, y + H/4), (x -1, y + 2*H/4), (x -1, y + 3*H/4)

b. (x-1, y), (x - 1, y+ 2*H/4), (x -1, y + 3*H/4), (x -1, y + H-1)

c. (x-1, y), (x -1, y + (2H)/4), (x -1, y + 2*(2H)/4), (x -1, y + 3*(2H) /4).

For example, when the left column is available or when the 1st bottom left selection is available.

d. (x-1, y), (x - 1, y+ 2*(2H)/4), (x -1, y + 3*(2H)/4), (x -1, y + (2H)- 1).

For example, when the bottom left column is available or when the 1st bottom left selection is available.

(iv) For the above examples, only two of the four samples can be selected.

(e) In one example, when the current mode is LM mode-A, then samples can be selected in accordance with Example 11(d)(ii).

(f) in one example, when the current mode is the LM-L mode, then samples can be selected in accordance with Example 11(d)(iii).

(g) The selected luminance samples (eg according to the selected chroma locations) can be grouped into 2 groups, one having the highest value and the lowest value of all selected samples, the other group consisting of all remaining samples.

(i) The two maximum values of the 2 groups are averaged as the maximum value in the 2-point method; the two minimum values of the 2 groups are averaged as the minimum value in the 2-point method to obtain the LM parameters.

(ii) When only 4 samples are selected, the two largest sample values are averaged, the two smallest sample values are averaged, and the averaged values are used as input values in the 2-point method to obtain the LM parameters.

Example 15: In the above examples, the brightness and chrominance can be switched. Alternatively, the luminance color component may be replaced by a primary color component (eg, G) and the chrominance color component may be replaced by a dependent color component (eg, B or R).

Example 16 It is proposed to select the top adjacent chrominance samples (and/or their corresponding luma samples, which may be downsampled) based on a first position offset value (denoted as F) and a step value (denoted as S). Assume that the width of the available top neighboring samples to use is W.

A. In one example, W could be set to the width of the current block.

b. In one example, W may be set to (L * width of the current block), in which L is an integer value.

With. In one example, when both top and left blocks are available, W can be set to the width of the current block.

i. Alternatively, when the left block is unavailable, W can be set to (L * width of the current block), in which L is an integer value.

ii. In one example, L may depend on the availability of the top right block. Alternatively, L may depend on the availability of one top-left sample.

d. In one example, W may depend on the coded mode.

i. In one example, W may be set to the width of the current block if the current block is encoded as LM mode;

ii. W can be set to (L * current block width), in which L is an integer value if the current block is encoded in LM-A mode.

- L may depend on the availability of the top right block. Alternatively, L may depend on the availability of one top-left sample.

e. Assume that the top left coordinate of the current block is (x0, y0), then select the top neighboring samples at positions (x0+F+K×S, y0-1) with K =0, 1, 2,…kMax.

f. In one example, F= W/P. P is an integer.

i. For example, P = 2 ⁱ , in which i is an integer such as 1 or 2.

ii. Alternatively, F = W/P + offset.

g. In one example, S = W/Q. Q is an integer.

i. For example, Q = 2 ^j , in which j is an integer such as 1 or 2.

h. For example, F = S/R. R is an integer.

i. For example, R = 2 ^M , in which M is an integer such as 1 or 2.

i. In one example, S = F/Z. Z is an integer.

i. For example, Z = 2 ⁿ , in which 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 (eg, 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 the availability of neighboring samples.

m. kMax and/or F and/or S and/or offset may depend on W.

n. For example, kMax = 1, F = W/4, S = W/2, offset= 0. Alternatively, in addition, the settings are made if the current block is LM encoded, both left and top adjacent samples are available, and W> = 4.

O. For example, kMax = 3, F = W/8, S = W/4, offset = 0. Alternatively, in addition, settings are made if the current block is to encode LM, only the top adjacent samples are available and W> = 4

R. For example, kMax = 3, F = W/8, S= W/4, offset = 0. Alternatively, in addition, the settings are made if the current block is LM-A coded and W> = 4.

q. For example, kMax = 1, F = 0, S = 1, offset = 0. Alternatively, in addition, the settings are made if W is 2.

Example 17 It is proposed to select the left adjacent chrominance samples (and/or their corresponding luma samples, which may be downsampled) based on a first position offset value (denoted by F) and a step value (denoted by S). Assume that the height of the available left neighboring samples to be used is H.

A. In one example, H could be set to the height of the current block.

b. In one example, H can be set to (L * height of the current block), in which L is an integer value.

With. In one example, when both top and left blocks are available, H can be set to the height of the current block.

i. Alternatively, when the top block is NOT available, H can be set to (L * height of the current block), in which L is an integer.

ii. In one example, L may depend on the availability of the lower left block. Alternatively, L may depend on the availability of one lower left sample.

iii. Alternatively, H can be set to (height of the current block + width of the current block) if accessibility of the top right adjacent blocks is required.

(a) In one example, the same H top neighbor samples are selected for LM-A mode and LM mode when left neighbor samples are not available.

d. In one example, H may depend on the coded mode.

i. In one example, H may be set to the height of the current block if the current block is encoded as LM mode;

ii. W can be set to (L * Height of the current block), in which L is an integer value if the current block is encoded in LM-L mode.

(a) L may depend on the availability of the lower left block. Alternatively, L may depend on the availability of one top-left sample.

(b). Alternatively, W can be set to (current block height + current block width) if the required lower left adjacent blocks are available.

(c) In one example, the same W left neighboring samples are selected for LM-L mode and LM mode when higher neighboring samples are not available.

e. Assume that the top left coordinate of the current block is (x0, y0), then select the left neighboring samples at positions (x0-1, y0+F+K×S) with K =0, 1, 2,…kMax

f. In one example, F = H/P. P is an integer.

i. For example, P = 2 ⁱ , in which i is an integer such as 1 or 2.

ii. Alternatively, F = H/P + offset.

g. In one example, S = H/Q. Q is an integer.

i. For example, Q = 2 ^J , in which j is an integer such as 1 or 2.

h. In one example, F = S/R. R is an integer.

i. For example, R = 2 ^M , in which M is an integer such as 1 or 2.

i. In one example, S = F/Z. Z is an integer.

i. For example, Z = 2 ⁿ , in which 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 (eg, 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 the availability of neighboring samples.

n. For example, kMax=1, F= H/4, S= H/2, offset = 0. Alternatively, in addition, the settings are made if the current block is LM encoded, both left and top adjacent samples are available and H>=4 .

O. For example, kMax=3, F= H/8, S= H/4, offset = 0. Alternatively, in addition, settings are made if the current block is LM encoded, only the top adjacent samples are available and H>=4

R. For example, kMax=3, F= H/8, S= H/4, offset = 0. Alternatively, in addition, the settings are made if the current block is encoded LM-L and H> = 4.

q. For example, kMax=1, F= 0, S= 1, offset = 0 if H is 2.

Example 18: Suppose that two or four adjacent chrominance samples (and/or their corresponding luminance samples, which may be downsampled) are selected to obtain the parameters of the linear model.

A. In one example, maxY/maxC and minY/minC are obtained from two or four adjacent chroma samples (and/or their corresponding luminance samples, which may be downsampled, and then used to obtain the linear model parameters using a 2-point approach.

b. In one example, given two adjacent chrominance samples (and/or their corresponding luma samples, which may be downsampled) that are selected to produce maxY/maxC and minY/minC, minY is set to the smallest luma sample value and minC is the corresponding chroma sample value; maxY is set to the largest luma sample value and maxC is its corresponding chrominance sample value.

With. In one example, given four adjacent chroma samples (and/or their corresponding luminance samples, which may be downsampled) that are selected to obtain maxY/maxC and minY/minC, the luminance samples and their corresponding chrominance samples are divided into two arrays G0 and G1, each containing two luma samples and their corresponding luma samples.

i. Suppose the four luma samples and their corresponding chroma samples are denoted as S0, S1, S2, S3, and they can be divided into two groups in any order. For example:

- G0={S0, S1}, G1={S2, S3};

- G0={ S1, S0}, G1={S3, S2};

- G0={S0, S2}, G1={S1, S3};

- G0={S2, S0}, G1={S3, S1};

- G0={S1, S2}, G1={S0, S3};

- G0={S2, S1}, G1={S3, S0};

- G0={S0, S3}, G1={S1, S2};

- G0={S3, S0}, G1={S2, S1};

- G0={S1, S3}, G1={S0, S2};

- G0={S3, S1}, G1={S2, S0};

- G0={S3, S2}, G1={S0, S1};

- G0={S2, S3}, G1={S1, S0};

(m) G0 and G1 can be variable.

ii. In one example, the value of the luma sample G0[0] and G0[1] are compared, if the value of the luma sample G0[0] is greater than the value of the luma sample G0[1], then the luma sample and its corresponding chrominance sample G0[0] will swap with G0[1].

(a) Alternatively, if the luminance sample value G0[0] is greater than or equal to the luminance sample value G0[1], then the luminance sample and its corresponding chrominance value G0[0] are interchanged with G0[1]

(b) Alternatively, if the luminance sample value G0[0] is less than the luminance sample value G0[1], then the luminance sample and its corresponding chrominance value G0[0] are interchanged with G0[1]

(c) Alternatively, if the luma sample value G0[0] is less than or equal to the luma sample value G0[1], the luma sample and its corresponding chrominance sample G0[0] will be swapped with G0[1].

iii. In one example, the luminance sample value of G1[0] and G1[1] are compared, if the luminance sample value of G1[0] is greater than the luminance sample value of G1[1], the luminance sample and its corresponding chrominance sample G1[0] will be swapped with G1 [1].

(a) Alternatively, if the luminance sample value G0[0] is greater than or equal to the luminance sample value G1[1], then the luminance sample and its corresponding chrominance value G1[0] are interchanged with G1[1]

(b) Alternatively, if the luminance sample value G1[0] is less than the luminance sample value G1[1], then the luminance sample and its corresponding chrominance value G1[0] are interchanged with G1[1]

(c) Alternatively, if the luma sample value of G1[0] is less than or equal to the luma sample value of G1[1], the luma sample and its corresponding chrominance sample G1[0] will be swapped with G1[1].

iv. One example compares the luminance sample value G0[0] and G1[1] if the luminance sample value G0[0] is greater than (or less than or not greater than or not less than) the luminance sample value G1[ 1], then G0 and G1 will change.

(a) In one example, the luminance sample value G0[0] and G1[0] are compared if the luminance sample value G0[0] is greater than (or less than or not greater than or not less than) the luminance sample value G1[0], then G0 and G1 will switch.

(b) One example compares the luminance sample value of G0[1] and G1[0] if the luminance sample value of G0[1] is greater than (or less than or not greater than or not less than) the luminance sample value of G1[ 0], then G0 and G1 will change.

(c) One example compares the luminance sample value of G0[1] and G1[1] if the luminance sample value of G0[1] is greater than (or less than or not greater than or not less than) the luminance sample value G1 [1], then G0 and G1 will change.

v. In one example, the luminance sample value G0[0] and G1[1] are compared if the luminance sample value G0[0] is greater than (or less than or not greater than or not less than) the luminance sample value G1[1], then G0[0] and G1[1] are swapped.

(a) In one example, the luminance sample value G0[0] and G1[0] are compared if the luminance sample value G0[0] is greater than (or less than or not greater than or not less than) the luminance sample value G1[0], then G0[0] and G1[0] will change.

(b) One example compares the luminance sample value of G0[1] and G1[0] if the luminance sample value of G0[1] is greater than (or less than or not greater than or not less than) the luminance sample value of G1[ 0], then G0 [1] and G1 [0] will change.

(c) One example compares the luminance sample value of G0[1] and G1[1] if the luminance sample value of G0[1] is greater than (or less than or not greater than or not less than) the luminance sample value G1 [1], then G0 [1] and G1 [1] will change.

vi. In one example, maxY is calculated as the average of the luma sample values G0[0] and G0[1], maxC is calculated as the average of the chroma sample values G0[0] and G0[1].

(a) Alternatively, maxY is calculated as the average of the luma sample values of G1[0] and G1[1], maxC is calculated as the average of the chroma sample values of G1[0] and G1[1].

vii. In one example, minY is calculated as the average of the luma sample values G0[0] and G0[1], minC is calculated as the average of the chroma sample values G0[0] and G0[1].

Alternatively, minY is calculated as the average of the luma samples of G1[0] and G1[1], minC is calculated as the average of the chrominance samples of G1[0] and G1[1].

d. In one example, if there are only two adjacent chroma samples (and/or their corresponding luma samples, which may be downsampled), they are first padded to produce four chroma samples (and/or their corresponding luma samples), then four chroma samples (and/or their corresponding brightness samples) are used to obtain the CCLM parameters.

i. In one example, two populated chroma samples (and/or their corresponding luma samples) are copied from two available adjacent chroma samples (and/or their corresponding luma samples, which may be downsampled).

Example 19: In all of the above examples, the selected chrominance samples must be located within the top row (i.e., with W samples), as shown in FIG. 10, and/or in the left column (i.e., with H samples), in where W and H represent the width and height of the current block.

A. Alternatively, the above limitation may be applied when the current block is encoded in normal LM mode.

b. Alternatively, the selected chrominance samples should be located within the top row (ie, with W samples) and the top right row with H samples.

i. Alternatively, in addition, the above limitation may be applied when the current block is encoded using LM-A mode.

ii. Alternatively, in addition, the above limitation can be applied when the current block is encoded using LM-A mode or normal LM mode with the top row accessible but the left column inaccessible.

With. Alternatively, the selected chrominance samples should be located in the left column (ie, with H samples) and the lower left column with W samples.

i. Alternatively, in addition, the above limitation may apply when the current block is encoded in LM-L mode.

ii. Alternatively, in addition, the above limitation can be applied when the current block is encoded using LM-L mode or normal LM mode with the top row inaccessible but the left column accessible.

Example 20

In one example, it is necessary to downsample only adjacent luma samples at positions where corresponding chrominance samples are required to obtain the CCLM parameters.

Example 21

How to perform the methods disclosed herein may depend on the color format (eg, 4:2:0 or 4:4:4).

A. Alternatively, how to perform the methods disclosed herein may depend on the bit depth (eg, 8-bit or 10-bit).

b. Alternatively, how to perform the methods disclosed herein may depend on the color representation method (eg, RGB or YCbCr).

With. Alternatively, how to perform the methods disclosed herein may depend on the color representation method (eg, RGB or YCbCr).

d. Alternatively, how to carry out the methods disclosed herein may depend on the location of the chroma downsampling.

Example 22

Whether or not to obtain the maximum/minimum values of the luma and chrominance components used to derive the CCLM parameters may depend on the availability of neighboring samples. For example, the maximum/minimum values for the luma and chrominance components used to obtain CCLM parameters cannot be obtained if both the left and top adjacent blocks are unavailable.

A. Whether to obtain the maximum/minimum values of the luma and chrominance components used to obtain the CCLM parameters may depend on the number of neighboring samples available. For example, the maximum/minimum values for the luma and chrominance components used to obtain the CCLMM parameters cannot be obtained if numSampL == 0 and numSampT == 0. In another example, the maximum/minimum values for the luma and chrominance components are used to obtain the CCLM parameters cannot be obtained if if numSampL + numSampT == 0. In the two examples, numSampL and numSampT are the number of available neighboring samples to the left and above the neighboring blocks.

b. Whether to obtain the maximum/minimum values of the luma and chrominance components used to obtain the CCLM parameters may depend on the number of selected samples used to obtain the parameters. For example, the maximum/minimum values for the luma and chrominance components used to obtain the CCLM parameters cannot be obtained if cntL == 0 and cntT == 0. In another example, the maximum/minimum values for the luma and chrominance components are used to obtain the CCLM parameters cannot be obtained if cntL + cntT == 0. In the two examples, cntL and cntT are the number of selected samples to the left and above the neighboring blocks.

Example 23

In one example, the proposed method for obtaining parameters used in CCLM can be used to obtain parameters used in LIC or other coding tools that apply a linear model.

A. The examples described above can be applied to LIC, for example, by replacing "adjacent chroma samples" with "adjacent samples of the current block" and replacing "corresponding luma samples" with "adjacent samples of the reference block".

b. In one example, the samples used to obtain the LIC parameter may exclude samples of certain positions in the top row and/or left column.

i. In one example, the samples used to obtain the LIC parameter may exclude the first one in the top row.

(a) Assuming the top left sample coordinate is (x0, y0), it is proposed to eliminate (x0, y0-1) to use LIC parameters.

ii. In one example, the samples used to obtain the LIC parameter may exclude the first one in the left column.

(a) Assuming the top left sample coordinate is (x0, y0), it is proposed to eliminate (x0-1, y0) to use LIC parameters.

iii. Whether the methods described above should be applied and/or how to determine specific items may depend on the availability of the left column/top row.

iv. Whether the above methods should be applied and/or how to determine specific positions may depend on the block size.

With. In one example, N neighboring samples (which may be downsampled) of the current block and N corresponding neighboring samples (which may be correspondingly downsampled) of the reference block may be used to obtain parameters used for LIC.

i. For example, N is 4.

ii. In one example, N adjacent samples can be defined as N/2 samples from the top row; and N/2 samples from the left column.

(a) Alternatively, N adjacent samples can be defined as N samples from the top row or left column.

iii. In another example, N is equal to min(L, T), in which T is the total number of available neighboring samples (which may be downsampled) of the current block.

(a) in one example L is set to 4

iv. In one example, selecting the coordinates of N samples may follow the rule for selecting N samples in a CCLM process.

v. In one example, selecting the coordinates of N samples may follow the rule for selecting N samples in the LM-A process.

vi. In one example, selecting the coordinates of N samples may follow the rule for selecting N samples in an LM-L process.

vii. In one example, how to select N samples may depend on the availability of the top row/left column.

d. In one example, N neighboring samples (which may be downsampled) of the current block and corresponding neighboring samples (which may be correspondingly downsampled) of the reference block may be selected to obtain parameters for use in the LIC based on the positions of the samples.

i. The selection method may depend on the width and height of the current block.

ii. The selection method may depend on the availability of neighboring blocks.

iii. For example, the K1 neighbor samples may be selected from the left neighbor samples and the K2 neighbor samples are selected from the top neighbor samples if both the top and left neighbor samples are available. For example. K1 = K2 = 2.

iv. For example, K1's neighbor samples may be selected from the left neighbor samples if only the left neighbor samples are available. For example, K1 = 4.

v. For example, K2 neighbor samples may be selected from the top neighbor samples if only the top neighbor samples are available. For example, K2 = 4.

vi. For example, top samples may be selected 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 neighboring blocks.

(a) For example, the methods disclosed in Example 16 can be used to produce F and S.

vii. For example, left samples may be selected 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 neighboring blocks.

(a) For example, the methods disclosed in paragraph 17 can be used to obtain F and S.

e. In one example, the proposed method for obtaining parameters used in CCLM can also be used to obtain parameters used in LIC when the current block is affine encoded.

f. The above methods can be used to obtain parameters used in other coding tools that rely on a linear model.

In another example, an inter-component prediction mode is proposed in which chroma samples are predicted with corresponding reconstructed luma samples according to the prediction model as shown in Equation 12. In Equation 12, Pred _C (x, y) denotes the prediction of the chroma sample. α and β are two parameters of the model. Rec'L(x, y) are downsampled luminance samples.

(12)

For the luminance downsampling process, a six-tap filter is applied to block A in Fig. 11, as shown in Equation 13.

(13)

The top surrounding luminance reference samples, shaded in FIG. 11, are not subject to the downsampling process using a 3-tap filter as shown in Equation 14. The left surrounding luminance reference samples are downsampled according to Equation 15. If the left or top samples are not available, there will be use the 2-tap filter defined in Equation 16 and Equation 17.

(14) (15) (16) (17)

In particular, the surrounding luma reference samples are subjected to a downsampling process to the same size of the chrominance reference samples. Size is indicated as width and height. Only two or four adjacent samples are used to obtain α and β. The lookup table is used to optionally perform a partition operation when obtaining α and β. The methods of obtaining are illustrated below.

3.1 Example methods for up to two samples

(1) The ratio r of width and height is calculated as shown in Equation 18

(18)

(2) If the top and left blocks are available, 2 samples located on posA of the first top line and posL of the first left line are selected. To simplify the description, the width is assumed to be the longer side. The derivation of posA and posL is shown in equation 19 (position index starts at 0). Figure 12 shows some examples of different widths and height ratios (1, 2, 4 and 8, respectively). Selected selections are shaded.

(19)

(3) If the top block is available when the left block is not available, the first and posA points of the top line are selected, as shown in Fig. 13

(4) if the left block is available when the top block is not available, the first and posL points of the left line are selected, as shown in Fig. 14

(5) obtain a chromaticity prediction model depending on the brightness and chromaticity values of the selected samples.

(6) if none of the left and top blocks are used, the default prediction model is used, with α equal to 0, β equal to 1 << (BitDepth-1), in which BitDepth represents the bit depth of the chroma samples.

3.2 Example methods for up to four samples

(1) The ratio r of width and height is calculated by Equation 18.

(2) If the top and left blocks are available, 4 samples located on the first and posA of the first top line, the first and posL of the first left line are selected. The production of posA and posL is illustrated in control 19. FIG. 15 shows some examples of different width and height ratios (1, 2, 4 and 8, respectively). Selected selections are shaded.

(3) If the top block is available when the left block is not available, the first and posA points of the top line are selected, as shown in Fig. 13.

(4) If the left block is available while the top block is not available, the first and posL points of the left line are selected, as shown in Fig. 14.

(5) If none of the left and top blocks are used, the default prediction model is used, α is 0, β is 1 << (BitDepth-1), in which BitDepth represents the bit depth of the chroma sample.

3.3 Example methods using lookup tables for LM retrieval

FIG. 16 shows an example of lookup tables with 128, 64 and 32 entries and each entry is represented by 16 bits. The 2-point LM acquisition process is simplified as shown in Table 1 and FIG. 17 with 64 entries. It should be noted that the first record may not be stored in the table.

It should also be noted that although each entry in the example tables is 16 bits, it can easily be converted to a number with smaller bits (e.g. 8 bits or 12 bits). For example, a table of entries with 8 bits could be obtained as:

g_aiLMDivTableHighSimp_64_8[i] = (g_aiLMDivTableHighSimp_64[i]+128) >> 8.

For example, a table of entries with 12 bits could be obtained as:

g_aiLMDivTableHighSimp_64_12[i] = (g_aiLMDivTableHighSimp_64[i]+8) >> 4.

Table 1: Simplified LM acquisition process

int iDeltaLuma = maxLuma – minLuma;

const int TABLE_PRECISION = 16; // It may be 8 or 12.

const int BIT_DEPTH = 10; // Bit depth for samples.

int shift = TABLE_PRECISION;

if( iDeltaLuma > 64) {

int depthshift = BIT_DEPTH - 6; // 64 is equal to 2^6.

iDeltaLuma = ( iDeltaLuma + (1<<(depthshift-1)))>> depthshift;

shift -= depthshift;

}

a = (((maxChroma – minChroma)*g_aiLMDivTableHighSimp_64[iDeltaLuma-1] + (1<<(shift-1)))>>shift;

It should be noted that maxLuma and minLuma can indicate the maximum and minimum values of the luminance samples of the selected positions. Alternatively, they may specify a function for maximum and minimum brightness sampling of selected positions, such as averaging. When only 4 positions are selected, they can also indicate the average of two larger brightness values and the average of two smaller brightness values. Additionally, as indicated in FIG. 17, maxChroma and minChroma represent chroma values corresponding to maxLuma and minLuma.

3.3 Method No. 4 up to four samples

Let's assume that the block width and height of the current block are W and H respectively. And the top left coordinate of the current chroma block is [0, 0].

If the top and left blocks are available and the current mode is the normal LM mode (excluding LM-A and LM-L), the 2 chroma samples located in the top row and the 2 chroma samples located in the left column are selected.

The coordinates of the top two samples are [floor(W/4), -1] and [floor (3*W/4), -1].

The coordinates of the two left samples are [-1, floor(H/4)] and [-1, floor (3*H/4)].

Selected samples are colored in red, as shown in Fig. 22A.

Subsequently, the 4 samples are sorted according to the brightness sample intensity and classified into 2 groups. Two large samples and two small samples are averaged respectively. The intercomponent prediction model is obtained with 2 averaged points. Alternatively, the maximum and minimum value of the four samples are used to obtain the LM parameters.

If the top block is available when the left block is not, four chroma samples are selected from the top block when W > 2 and 2 chroma samples are selected when W = 2.

The coordinates of the four selected top samples are [[W/8, -1], [W/8 + W/4, -1], [W/8 + 2*W/4, -1] and [W/8 + 3 *W/4, -1].

Selected samples are colored red as shown in Fig. 22B.

If the left block is available when the top block is not, four chroma samples are selected from the left block when H > 2 and 2 chroma samples when H = 2.

The coordinates of the selected four left samples are [-1, H/8], [-1, H/8 + H/4], [-1, H/8 + 2*H/4, -1] and [-1, H/8 + 3*H/4].

If none of the left and top blocks are available, the default prediction is used, with α equal to 0, β equal to 1 << (BitDepth-1), in which BitDepth represents the bit depth of the chroma samples.

If the current mode is LM-A mode, four chrominance samples are selected from the top block when W' > 2 and 2 chroma samples are selected when W' = 2. W' is the available number of top adjacent samples, which can be 2 * W.

The coordinates of the four selected top samples are [W'/8, -1], [W'/8 + W'/4, -1], [W'/8 + 2*W'/4, -1] and [W '/8 + 3*W'/4, -1].

If the current mode is the LM-L mode, four chrominance samples are selected from the left block when chrominance samples are selected at H'=2. H' is the available number of left neighboring samples, which can be 2 * H.

The coordinates of the four selected top samples are [-1, H'/8], [-1, H'/8 + H'/4], [-1, H'/8 + 2*H'/4, -1] and [-1, H'/8 + 3*H'/4 ].

3.5 Example of an implementation for modifying the current VVC standard to use CCLM prediction.

8.3.4.2.8 Specification INTRA_LT_CCLM, INTRA_L_CCLM and INTRA_T_CCLM intra prediction mode

The equations are described in this section using equation numbering corresponding to those used in the current draft of the VVC standard.

Inputs in process:

- internal prediction mode predModeIntra.

- sample location (xTbC, yTbC ) of the top left sample of the current transform block relative to the top left sample of the current image,

- nTbW variable indicating the width of the conversion block,

- nTbH variable indicating the height of the transformation block,

- adjacent chromaticity samples p [x][y], with x = −1, y = 0..2 * nTbH − 1 and x = 0.. 2 * nTbW − 1, y = − 1.

The output of this process is the predicted samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH − 1

The current brightness location (xTbY, yTbY) is obtained as follows:

The variables availL, availT and availTL are obtained as follows:

...

- If PredModeIntra is equal to INTRA_LT_CCLM, the following applies:

numSampT = availT ? nTbW: 0 (8-156)

numSampL = availL ? nTbH: 0 (8-157)

- Otherwise the following applies:

numSampT = (availT && predModeIntra = = INTRA_T_CCLM ) ?
(nTbW + numTopRight ):0 (8-158)

The bCTUboundary variable is obtained as follows:

bCTUboundary = (yTbC & (1 << ( CtbLog2SizeY − 1 ) − 1 ) = = 0 ) ? TRUE: FALSE. (8-160)

Prediction samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH − 1 are obtained as follows:

- If both numSampL and numSampT are 0, the following applies:

predSamples[ x ][ y ] = 1 << ( BitDepth _C − 1 ) (8-161)

- Otherwise, the following ordered steps apply:

1. ... [[No change to current specification]

2. ...

3. ...

4. ...

5. ...

6. ...... [No change to current specification]

7. The variables minY, maxY, minC and maxC are obtained as follows:

- The minY variable is set to 1 << (BitDEpthy) + 1 and the maxY variable is set to -1.

- If availL is TRUE and predModeIntra is INTRA_LT_CCLM, the variable aboveIs4 is set to 0; otherwise it is set to 1.

- If availT is TRUE and predModeIntra is INTRA_LT_CCLM, the LeftIs4 variable is set to 0; otherwise it is set to 1.

- The startPos[] and pickStep[] array variables are obtained as follows:

- startPos[0] = actualTopTemplateSampNum >> (2 + aboveIs4);

- pickStep[0] = std::max(1, actualTopTemplateSampNum >> (1 + aboveIs4));

- startPos[1] = actualLeftTemplateSampNum >> (2 + leftIs4);

- pickStep[1] = std::max(1, actualLeftTemplateSampNum >> (1 + leftIs4));

- The cnt variable is set to 0.

- If predModeIntra is equal to INTRA_LT_CCLM, the variable nSX is set to nTbW, nSY is set to nTbH;; Otherwise, nSX is set to numSampLT and nSY is set to numSampL.

- If availT is TRUE and predModeIntra is not equal to INTRA_L_CCLM, the selectLumaPix, selectChromaPix variables are obtained as follows:

- When startPos[0]+cnt* pickStep[0] < nSX and cnt < 4, the following applies:

- - selectLumaPix[cnt] = pTopDsY[ startPos[0]+cnt* pickStep[0]];

- selectChromaPix[cnt]= p[startPos[0]+cnt* pickStep[0]][ −1 ];

- cnt++;

- If availL is TRUE and predModeIntra is not equal to INTRA_T_CCLM, the selectLumaPix, selectChromaPix variables are obtained as follows:

- - When startPos[1]+cnt* pickStep[1] < nSY and cnt < 4, the following applies:

- selectLumaPix[cnt] = pLeftDsY [ startPos[1]+cnt* pickStep[1] ];

- selectChromaPix[cnt]= p[-1][ startPos[1]+cnt* pickStep[1]];

- cnt++;

- If cnt is 2, the following applies:

- If selectLumaPix[0] > selectLumaPix[1], minY is set to selectLumaPix[1], minC is set to selectChromaPix[1], maxY is set to selectLumaPix[0] and maxC is set to selectChromaPix[0]; otherwise, maxY is set to selectLumaPix[1], maxC is set to selectChromaPix[1], minY is set to selectLumaPix[0], and minC is set to selectChromaPix[0].

- Otherwise, if cnt is 4, the following applies:

- The array variables minGrpIdx and maxGrpIdx are initialized as:

- minGrpIdx[0] = 0, minGrpIdx[1] = 1, maxGrpIdx[0] = 2, maxGrpIdx[1] = 3;

- the following applies

- If selectLumaPix[minGrpIdx[0]] > selectLumaPix[minGrpIdx[1]], replace minGrpIdx[0] and minGrpIdx[1];

- If selectLumaPix[maxGrpIdx[0]] > selectLumaPix[maxGrpIdx[1]], replace maxGrpIdx[0] and maxGrpIdx[1];

- If selectLumaPix[minGrpIdx[0]] > selectLumaPix[maxGrpIdx[1]], replace minGrpIdx and maxGrpIdx;

- If selectLumaPix[minGrpIdx[1]] > selectLumaPix[maxGrpIdx[0]], replace minGrpIdx[1] and maxGrpIdx[0];

- maxY, maxC, minY and minC are obtained as follows:

- maxY =(selectLumaPix[maxGrpIdx[0]]+selectLumaPix[maxGrpIdx[1]]+1)>>1;

- maxC =(selectChromaPix[maxGrpIdx[0]]+selectChromaPix[maxGrpIdx[1]]+1)

>>1;

- maxY =(selectLumaPix[minGrpIdx [0]]+selectLumaPix[minGrpIdx [1]]+1)>>1;

- maxC =(selectChromaPix[minGrpIdx[0]]+ selectChromaPix [minGrpIdx [1]]+1)>>1;

8. Variables a, b and k are obtained as follows:

[end of change]

3.6 Another sample working design for CCLM's proposed prediction

This section describes another exemplary embodiment that shows modifications that can be made to the current working draft of the VVC standard. The equation numbers here refer to the corresponding equation numbers in the VVC standard.

Specification of INTRA_LT_CCLM, INTRA_L_CCLM and INTRA_T_CCLM intra prediction mode.

[Add to current VVC working project as below]

The number of available neighboring chroma samples on the top and top-right numTopSamp and the number of available neighboring chroma samples on the left and bottom-left nLeftSamp are obtained as follows:

- If PredModeIntra is equal to INTRA_LT_CCLM, the following applies:

numSampT = availT ? nTbW: (8-157) numSampL = availL ? nTbH (8-158)

- Otherwise the following applies:

numSampT = ( availT && predModeIntra = = INTRA_T_CCLM ) ?
( nTbW + Min( numTopRight, nTbH )) : 0 (8-159) numSampL = ( availL && predModeIntra = = INTRA_L_CCLM ) ?
( nTbH + Min( numLeftBelow, nTbW )) : 0 (8-160)

The bCTUboundary variable is obtained as follows:

bCTUboundary = ( yTbC & ( 1 << ( CtbLog2SizeY − 1 ) − 1 ) = = 0 ) ? TRUE: FALSE. (8-161)

The variable cntN and the array pickPosN[] with N replaced by L and T are obtained as follows:

- The variable numIs4N is set to ((availN && predModeIntra == INTRA_LT_CCLM ) ? 0 : 1).

- The variable startPosN is set to numSampN >> ( 2 + numIs4N ).

- The variable pickStepN is set to Max(1, numSampN >> ( 1 + numIs4N )).

- - If availN is TRUE and predModeIntra is INTRA_LT_CCLM or INTRA_N_CCLM, cntN is set to ( 1 + numIs4N ) << 1, and pickPosN[ pos ] is set to (startPosN + pos * pickStepN), with pos = 0..( cntN – 1 ).

- Otherwise cntN is set to 0.

Prediction samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH − 1 are obtained as follows:

- If both numSampL and numSampT are 0, the following applies:

predSamples[ x ][ y ] = 1 << ( BitDepth _C − 1 ) (8-162)

- Otherwise, the following ordered steps apply:

1. Co-located brightness samples pY[ x ][ y ] with x = 0..nTbW * 2 − 1, y= 0..nTbH * 2 − 1 are set equal to the reconstructed brightness samples before the deblocking filtering process at locations ( xTbY + x , yTbY + y).

2. Neighboring brightness samples pY[ x ][ y ] are obtained as follows:

- When numSampL is greater than 0, the adjacent left luminance samples pY[ x ][ y ] with x = −1..−3, y = 0..2 * numSampL − 1, are set equal to the reconstructed luminance samples before the deblocking filtering process at locations ( xTbY + x , yTbY +y ).

- When numSampT is greater than 0, adjacent top luminance samples pY[ x ][ y ] with x = 0..2 * numSampT − 1, y = −1, −2, are set equal to the reconstructed luminance samples before the deblocking filtering process at locations ( xTbY+ x, yTbY + y ).

- When availTL is TRUE, the adjacent top left luminance samples pY[ x ][ y ] with x = −1, y = −1, −2 are set equal to the reconstructed luminance samples before the deblocking filtering process at locations ( xTbY+ x, yTbY + y ) .

3. Co-located brightness samples after downsampling pDsY[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH – 1 are obtained as follows:

- If sps_cclm_colocated_chroma_flag is 1, the following applies:

- pDsY[ x ][ y ] with x = 1..nTbW − 1, y = 1..nTbH − 1 is obtained as follows:

pDsY[x][y] = (pY[2*x][2*y−1] +
pY[2*x −1][2*y] + 4*pY[2*x][2*y] + pY[2*x + 1][2*y] + pY[2*x][2 *y +1] + 4 ) >> 3 (8-163)

- If availL is TRUE, pDsY[ 0 ][ y ] with y = 1..nTbH − 1 is obtained as follows:

pDsY[0][y]=(pY[0][2*y−1] +
pY[ −1 ][2*y] + 4*pY[0][2*y ] + pY[1][2*y ] + pY[0][2*y + 1] + 4) >> 3 (8-164)

- Otherwise, pDsY[ 0 ][ y ] with y = 1..nTbH − 1 is obtained as follows:

pDsY[0][y] = (pY[0][2*y − 1] + 2*pY[0][2*y] + pY[0][2*y + 1] + 2) >> 2 (8-165)

- If availT is TRUE, pDsY[ x ][ 0 ] with x = 1..nTbW − 1 is obtained as follows:

- pDsY[x][0]=(pY[2*x][−1] +
pY[2*x−1][0]+4*pY[2*x][0]+pY[2*x+1][0] +
pY[2*x][1] + 4) >> 3 (8-166)

- Otherwise, pDsY[ x ][ 0 ] with x = 1..nTbW − 1 is obtained as follows:

pDsY[x][0] = (pY[2*x −1][0] + 2*pY[2*x][0] + pY[2*x + 1][0] +2) >> 2 (8-167)

- If availL is TRUE and availT is TRUE, pDsY[ 0 ][ 0 ] is obtained as follows:

- pDsY[0][0]=(pY[0][−1] +
pY[−1][0] + 4*pY[0][0] + pY[1][0] + pY[0][1] + 4) >> 3 (8-168)

- Otherwise, if availL is TRUE and availT is FALSE, pDsY[ 0 ][ 0 ] is obtained as follows:

- pDsY[0][0] = (pY[−1][0] + 2*pY[0][0] + pY[1][0] + 2) >> 2 (8-169)

- Otherwise, if availL is FALSE and availT is TRUE, pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[0][0] = (pY[0][−1] +2*pY[0][0] +pY[0][1] + 2) >> 2 (8-170)

- Otherwise (availL is FALSE and availT is FALSE), pDsY[ 0 ][ 0 ] is obtained as follows:

- pDsY[0][0] = pY[0][0] (8-171)

- Otherwise, the following applies:

- pDsY[ x ][ y ] with x = 1..nTbW − 1, y = 0..nTbH − 1 was obtained using the following formula:

- pDsY[x][y] = (pY[2*x − 1][2*y] + pY[2*x−1][2*y+1] +
2* pY[2* x][2*y] + 2*pY[2*x][2* y + 1] + pY[2* x + 1][2*y] + pY[2*x + 1][2*y + 1] + 4) >> 3 (8-172)

- If availL is TRUE, pDsY[ 0 ][ y ] with y = 0..nTbH − 1 is obtained as follows:

- pDsY[0][y] = (pY[−1][2*y] + pY[−1][2*y+1] +
2*pY[0][2*y]+2*pY[0][2*y+1] +
pY[1][2*y] + pY[1][2*y + 1] + 4) >> 3 (8-173)

- Otherwise, pDsY[ 0 ][ y ] with y = 0..nTbH − is obtained as follows:

- pDsY[0][y] = (pY[0][2*y] + pY[0][2*y + 1] + 1) >> 1 (8-174)

4. When numSampL exceeds 0, the selected co-left color samples pSelC[idx] are set to p[-1][pickPosL[idx]] with idx = 0..(cntL – 1), and the selected adjacent left luminance samples after downsampling pSelDsY[ idx ] with idx = 0..(cntL-1) are obtained using the following format:

- variable y is set equal to pickPosL[ idx ].

- if sps_cclm_colocated_chroma_flag is 1, then the following applies:

- if y > 0 || availTL == TRUE,

pSelDsY[idx]=(pY[−2][2*y−1] +
pY[−3][2*y] + 4*pY[−2][2*y]+pY[−1][2*y] +
pY[−2][ 2* y + 1] + 4) >> 3 (8-175)

- otherwise,

pSelDsY[ idx ] = ( pY[ −3 ][ 0 ] + 2 * pY[ −2 ][ 0 ] + pY[ −1 ][ 0 ] + 2 ) >> 2 (8-177)

- otherwise, the following applies:

pSelDsY[idx] = (pY[−1][2*y]+pY[−1][2*y+1] +
2* pY[−2][2*y]+2*pY[−2][2*y+1] +
pY[ −3 ][ 2 * y ] + pY[ −3 ][ 2 * y + 1 ] + 4 ) >> 3 (8-178)

5. When numSampT is greater than 0, the selected neighboring top chrominance samples pSelC[idx] are set to p[ pickPosT[ idx ]][ -1 ] with idx = 0..( cntT – 1 ), and the neighboring top luminance samples after downsampling pSelDsY [ idx ] with idx = cntL..(cntL + cntT – 1) are defined as below:

- variable x is set to pickPosT[ idx - cntL ].

- if sps_cclm_colocated_chroma_flag is 1, then the following applies:

- if x > 0:

- if bCTUboundary is FALSE, then the following applies:

pSelDsY[idx]=(pY[2*x][−3] +
pY[2*x − 1][−2] + 4*pY[2*x][−2] + pY[2*x + 1][−2] +
pY[2 * x][ −1] + 4) >> 3 (8-179)

- otherwise (bCTUboundary is TRUE), the following applies:

pSelDsY[idx]=(pY[2*x−1][−1] +
2* pY[2 * x ][ −1 ] + pY[2 * x + 1][ −1] + 2) >> 2 (8-180)

- otherwise:

- if availTL is TRUE and bCTUboundary is FALSE, then the following applies:

pSelDsY[idx]=(pY[0][−3]+
pY[−1][−2]+4*pY[0][−2]+pY[1][−2] +
pY[0][−1] + 4) >> 3 (8-181)

otherwise, if availTL is TRUE and bCTUboundary is TRUE, then the following applies:

pSelDsY[idx]=(pY[−1][−1] +
2* pY[0][−1] + pY[1][−1] + 2) >> 2 (8-182)

- otherwise, if availTL is FALSE and bCTUboundary is FALSE, then the following applies:

pSelDsY[ idx ] = ( pY[ 0 ][ −3 ] + 2 * pY[ 0 ][ −2 ] + pY[ 0 ][ −1 ] + 2 ) >> 2 (8-183)

- otherwise (availTL is FALSE and bCTUboundary is TRUE), the following applies:

pSelDsY[ idx ] = pY[ 0 ][ −1 ] (8-184)

- otherwise, the following applies:

-if x > 0:

- if bCTUboundary is FALSE, then the following applies:

pSelDsY[idx] = (pY[2*x−1][−2] + pY[2*x−1][−1] +
2*pY[2*x][−2]+2*pY[2*x][−1] +
pY[2*x + 1][ −2] + pY[2* x + 1][ −1] + 4) >> 3 (8-185)

-otherwise (bCTUboundary is TRUE), then the following applies:

pSelDsY[idx]=(pY[2*x−1][−1] +
2*pY[2*x][−1]+ pY[2* x + 1][ −1] + 2) >> 2 (8-186)

-otherwise:

- if availTL is TRUE and bCTUboundary is FALSE, then the following applies:

pSelDsY[idx]=(pY[−1][−2]+pY[−1][−1] +
2* pY[ 0 ][ −2 ] + 2*pY[ 0 ][ −1 ] + pY[ 1 ][ −2 ] + pY[ 1 ][ −1 ] + 4) >> 3 (8-187)

- otherwise, if availTL is TRUE and bCTUboundary is TRUE, then the following applies:

pSelDsY[idx]=(pY[−1][−1] +
2* pY[0][ −1 ] + pY[ 1 ][ −1 ] + 2) >> 2 (8-188)

-otherwise, if availTL is FALSE and bCTUboundary is FALSE, then the following applies:

pSelDsY[ idx ] = ( pY[ 0 ][ −2 ] + pY[ 0 ][ −1 ] + 1 ) >> 1 (8-189)

-otherwise (availTL is FALSE and bCTUboundary is TRUE), the following applies:

pSelDsY[ idx ] = pY[ 0 ][ −1 ] (8-190)

6. The variables minY, maxY, minC and maxC are obtained as follows:

-

- when cntT+cntL is 2, set pSelC[idx + 2] = pSelC[idx] and pSelDsY[idx + 2] = pSelDsY[idx], with idx = 0 and 1.

- minGrpIdx[] and maxGrpIdx[] arrays are set as: minGrpIdx[0] = 0, minGrpIdx[1] = 1, maxGrpIdx[0] = 2, maxGrpIdx[1] = 3.

-if pSelDsY[minGrpIdx[0]] > pSelDsY[minGrpIdx[1]], change (minGrpIdx[0], minGrpIdx[1]).

-if pSelDsY[maxGrpIdx[0]] > pSelDsY[maxGrpIdx[1]], change (maxGrpIdx[0], maxGrpIdx[1]).

-if pSelDsY[minGrpIdx[0]] > pSelDsY[maxGrpIdx[1]], change (minGrpIdx, maxGrpIdx ).

-if pSelDsY[minGrpIdx[1]] > pSelDsY[maxGrpIdx[0]], change (minGrpIdx[1], maxGrpIdx[0]).

-maxY = ( pSelDsY[maxGrpIdx[0]] + pSelDsY[maxGrpIdx[1]] + 1 ) >> 1.

-maxC = ( pSelC[maxGrpIdx[0]] + pSelC[maxGrpIdx[1]] + 1 ) >> 1.

-minY = ( pSelDsY[minGrpIdx[0]] + pSelDsY[minGrpIdx[1]] + 1 ) >> 1.

-minC = ( pSelC[minGrpIdx[0]] + pSelC[minGrpIdx[1]] + 1 ) >> 1.

7. Variables a, b and k are obtained as follows:

- If numSampL is 0 and numSampT is 0, the following applies:

k = 0 (8-208) a = 0 (8-209) b = 1 << ( BitDepth _C − 1) (8-210)

- Otherwise, the following applies:

diff = maxY − minY (8-211)

- If diff is not 0, the following applies:

- diffC = maxC − minC (8-212) x = Floor(Log2(diff) (8-213) normDiff = ( ( diff << 4 ) >> x ) & 15 (8-214) x +=(normDiff != 0) ? 10 (8-215) y = Floor (Log2( Abs(diffC) ) ) + 1 (8-216) a = ( diffC * ( divSigTable [normDiff ] | 8) + 2 ^{y − 1} ) >>y (8-217) k = ( ( 3 + x − y ) < 1 ) ? 1 : 3 + x − y (8-218) a = ( ( 3 + x − y ) < 1 ) ? Sign(a) *15 : a (8-219) b = minC − ( (a * minY) >> k) (8-220)

de divSigTable[ ] is specified according to:

divSigTable[ ] = { 0, 7, 6, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 1, 1, 0 } (8-221)

- otherwise (diff equals 0), the following applies:

- k = 0 (8-222) a = 0 (8-223) b = minC (8-224)

8. Prediction samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0.. nTbH − 1 are obtained as follows:

predSamples[ x ][ y ] = Clip1C( ( ( pDsY[ x ][ y ] * a ) >> k ) + b ) (8-225)

[end example embodiment]

3.7 Another rough draft of CCLM's proposed prediction

This section describes another exemplary embodiment that shows modifications that can be made to the current working draft of the VVC standard. The equation numbers here refer to the corresponding equation numbers in the VVC standard.

Specification of INTRA_LT_CCLM, INTRA_L_CCLM and INTRA_T_CCLM intra prediction mode

...

The number of available neighboring chroma samples on the top and top-right numTopSamp and the number of available neighboring chroma samples on the left and bottom-left nLeftSamp are obtained as follows:

- if predModeIntra is equal to INTRA_LT_CCLM, the following applies:

numSampT = availT ? nTbW: 0 (8-157) numSampL = availL ? nTbH: 0 (8-158)

- otherwise, the following applies:

numSampT = ( availT && predModeIntra = = INTRA_T_CCLM ) ?

( nTbW + Min( numTopRight, nTbH )) : 0 (8-159)

numSampL = ( availL && predModeIntra = = INTRA_L_CCLM ) ?

( nTbH + Min( numLeftBelow, nTbW )) : 0 (8-160)

The bCTUboundary variable is obtained as follows:

bCTUboundary = (yTbC & (1 << ( CtbLog2SizeY − 1 ) − 1 ) = = 0 ) ? TRUE: FALSE. (8-161)

The variable cntN and the array pickPosN[] with N replaced by L and T are obtained as follows:

-Variable numIs4N is set to (( availN && predModeIntra == INTRA_LT_CCLM ) ? 0 : 1).

- Variable startPosN is set to numSampN >> ( 2 + numIs4N ).

-The variable pickStepN is set to Max( 1, numSampN >> ( 1 + numIs4N )).

- if availN is TRUE and predModeIntra is INTRA_LT_CCLM or INTRA_N_CCLM, cntN is set to Min( numSampN, ( 1 + numIs4N ) << 1 ), and pickPosN[ pos ] is set to (startPosN + pos * pickStepN), with pos = 0.. (cntN – 1).

- otherwise, cntN is set to 0.

Prediction samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH − 1 are obtained as follows:

-if both numSampL and numSampT are 0, the following applies:

predSamples[ x ][ y ] = 1 << ( BitDepthC − 1 ) (8-162)

- otherwise, the following ordered steps apply:

1.Co-located brightness samples pY[ x ][ y ] with x = 0..nTbW * 2 − 1, y= 0..nTbH * 2 − 1 are set equal to the reconstructed brightness samples before performing the deblocking filtering process on locations ( xTbY + x, yTbY + y ).

2. Neighboring brightness samples pY[ x ][ y ] are obtained as follows:

-when numSampL is greater than 0, adjacent left luminance samples pY[ x ][ y ] with x = −1..−3, y = 0..2 * numSampL − 1 are set equal to the reconstructed luminance samples before performing the deblocking filtering process on locations ( xTbY + x , yTbY +y ).

-when numSampT is greater than 0, adjacent top luminance samples pY[ x ][ y ] with x = 0..2 * numSampT − 1, y = −1, −2, are set equal to the reconstructed luminance samples before performing the deblocking filtering process on locations ( xTbY+ x, yTbY + y ).

-when availTL is TRUE, the adjacent upper left luminance samples pY[ x ][ y ] with x = −1, y = −1, −2 are set equal to the reconstructed luminance samples before performing the deblocking filtering process on locations ( xTbY+ x, yTbY + y).

3. Co-located brightness samples after downsampling pDsY[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH − 1 are obtained as follows:

-if sps_cclm_colocated_chroma_flag is 1, the following applies:

-pDsY[ x ][ y ] with x = 1..nTbW − 1, y = 1..nTbH − 1 are described as below:

pDsY[x][y]=(pY[2*x][2*y−1] +
pY[ 2 * x − 1][2* y] + 4 * pY[2* x][2 * y] + pY[2 * x + 1][2 * y] + pY[2* x][2 * y + 1] + 4) >> 3 (8-163)

-if availL is TRUE, pDsY[ 0 ][ y ] with y = 1..nTbH − 1 is obtained as follows:

pDsY[ 0 ][ y ] = ( pY[ 0 ][ 2 * y − 1 ] +
pY[ −1 ][ 2 * y ] + 4 * pY[ 0 ][ 2 * y ] + pY[ 1 ][ 2 * y ] + (8-164)
pY[ 0 ][ 2 * y + 1 ] + 4 ) >> 3 (8-164)

-otherwise, pDsY[ 0 ][ y ] with y = 1..nTbH − 1 is obtained as follows:

pDsY[0][ y ] = (pY[0][2 * y − 1] + 2 * pY[0][2 * y] + pY[0][2 * y + 1] + 2) >> 2 (8-165)

-if availT is TRUE, pDsY[ x ][ 0 ] with x = 1..nTbW − 1 is obtained as follows:

pDsY[x][0]=(pY[2*x][−1]+
pY[2*x−1][0]+4*pY[2*x][0]+pY[2*x+1][0] +
pY[ 2 * x ][ 1 ] + 4 ) >> 3 (8-166)

-otherwise, pDsY[ x ][ 0 ] with x = 1..nTbW − 1 is obtained as follows:

pDsY[ x ][ 0 ] = ( pY[ 2 * x − 1 ][ 0 ] + 2 * pY[ 2 * x ][ 0 ] + pY[ 2 * x + 1 ][ 0 ] + 2 ) >> 2 (8-167)

-if availL is TRUE and availT is TRUE, pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[0][0]=(pY[0][−1] +pY[−1][0]+4*pY[0][0]+pY[1][0]+
pY[ 0 ][ 1 ] + 4) >> 3 (8-168)

-otherwise, if availL is TRUE and availT is FALSE, pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[ 0 ][ 0 ] = ( pY[ −1 ][ 0 ] + 2 * pY[ 0 ][ 0 ] + pY[ 1 ][ 0 ] + 2 ) >> 2 (8-169)

-otherwise, if availL is FALSE and availT is TRUE, pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[ 0 ][ 0 ] = ( pY[ 0 ][ −1 ] + 2 * pY[ 0 ][ 0 ] + pY[ 0 ][ 1 ] + 2 ) >> 2 (8-170)

-otherwise, (availL is FALSE and availT is FALSE), pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[ 0 ][ 0 ] = pY[ 0 ][ 0 ] (8-171)

-otherwise, the following applies:

pDsY[ x ][ y ] with x = 1..nTbW − 1, y = 0..nTbH − 1 is obtained as follows:

pDsY[ x ][ y ] = ( pY[ 2 * x − 1][ 2 * y ] + pY[ 2 * x − 1][ 2 * y + 1] +
2* pY[2 * x][2 * y] + 2*pY[ 2 * x][2 * y + 1] + pY[ 2 * x + 1][ 2 * y] + pY[ 2 * x + 1][2 * y + 1] + 4 ) >> 3 (8-172)

-if availL is TRUE, pDsY[ 0 ][ y ] with y = 0..nTbH − 1 is obtained as follows:

pDsY[0][y]=(pY[−1][2*y]+pY[−1][2*y+1]+
2* pY[ 0 ][ 2 * y ] + 2*pY[ 0 ][ 2*y + 1] + pY[1][ 2 * y] + pY[1][2*y + 1] + 4) >>3 (8-173)

-otherwise, pDsY[ 0 ][ y ] with y = 0..nTbH − 1 is obtained as follows:

pDsY[ 0 ][ y ] = ( pY[ 0 ][ 2 * y ] + pY[ 0 ][ 2 * y + 1 ] + 1 ) >> 1 (8-174)

4. When numSampL is greater than 0, the selected neighboring left chroma samples pSelC[idx] are set to p[ -1 ][ pickPosL[ idx ]] with idx = 0..(cntL – 1) and the selected neighboring left luminance samples after downsampling pSelDsY [ idx ] with idx = 0..(cntL-1) is obtained as follows:

-variable y is set to pickPosL[idx].

-if sps_cclm_colocated_chroma_flag is 1, the following applies:

-if y > 0 || availTL == TRUE,

pSelDsY[idx]=(pY[−2][2*y−1] +
pY[ −3][2* y] + 4* pY[ −2][2*y] + pY[ −1][2* y] + pY[ −2][2 * y + 1] + 4) >>3 (8-175)

-otherwise,

pSelDsY[ idx ] = (pY[−3][0] + 2* pY[−2][0] + pY[ −1][0] + 2) >> 2 (8-177)

-otherwise, the following applies:

pSelDsY[idx] = (pY[−1][2*y] + pY[−1][2*y+1] +
2* pY[−2][2 * y] + 2*pY[−2][2* y + 1] + pY[ −3][2* y] + pY[ −3][2*y + 1 ] + 4) >> 3 (8-178)

5. When numSampT is greater than 0, the selected neighboring top chrominance samples pSelC[idx] are set to p[ pickPosT[ idx ]][ -1 ] with idx = 0..( cntT – 1 ), and the neighboring top luminance samples after downsampling pSelDsY [ idx ] with idx = cntL..(cntL + cntT – 1) are specified as follows:

-variable x is set equal to pickPosT[ idx - cntL ].

-if sps_cclm_colocated_chroma_flag is 1, the following applies:

-if x > 0:

-if bCTUboundary is FALSE the following applies:

pSelDsY[idx]=(pY[2*x][−3]+
pY[2*x − 1][ −2] + 4 * pY[2 * x][ −2] + pY[2* x + 1][ −2] + pY[2* x][−1] + 4) >> 3 (8-179)

-otherwise (bCTUboundary is TRUE), the following applies:

pSelDsY[idx]=(pY[2*x−1][−1]+
2* pY[2* x][ −1] + pY[ 2 * x + 1][ −1] + 2) >> 2 (8-180)

-otherwise:

-if availTL is TRUE and bCTUboundary is FALSE, the following applies:

pSelDsY[idx]=(pY[0][−3] +
pY[−1][ −2] + 4* pY[0][−2] + pY[1][−2] + pY[0][−1] + 4 ) >> 3 (8-181)

-otherwise, if availTL is TRUE and bCTUboundary is TRUE, the following applies:

pSelDsY[idx]=(pY[−1][−1] +
2* pY[0][−1] + pY[1][ −1] + 2) >> 2 (8-182)

- otherwise, if availTL is FALSE and bCTUboundary is FALSE, the following applies:

pSelDsY[idx] = (pY[0][−3] + 2* pY[0][ −2] + pY[0][ −1] + 2) >> 2 (8-183)

-otherwise (availTL is FALSE and bCTUboundary is TRUE), the following applies:

pSelDsY[ idx ] = pY[ 0 ][ −1 ] (8-184)

-otherwise, the following applies:

-if x > 0:

-if bCTUboundary is FALSE, the following applies:

pSelDsY[idx] = (pY[2*x−1][−2] + pY[2*x−1][−1] +
2* pY[ 2 * x ][ −2 ] + 2*pY[ 2 * x][ −1 ] + pY[2* x + 1][ −2 ] + pY[2 * x + 1][ −1 ] + 4) >> 3 (8-185)

-otherwise, (bCTUboundary is TRUE), the following applies:

pSelDsY[idx]=(pY[2*x−1][−1] +
2* pY[ 2 * x ][ −1] + pY[ 2 * x + 1][ −1 ] + 2 ) >> 2 (8-186)

-otherwise:

-if availTL is TRUE and bCTUboundary is FALSE, the following applies:

pSelDsY[idx]=(pY[−1][−2]+pY[−1][−1] +
2* pY[0][ −2] + 2*pY[0][ −1] + pY[1][−2] + pY[1][ −1] + 4) >> 3 (8-187)

-otherwise, if availTL is TRUE and bCTUboundary is TRUE, the following applies:

pSelDsY[idx]=(pY[−1][−1] +
2* pY[0][−1] + pY[1][−1 + 2) >> 2 (8-188)

-otherwise, if availTL is FALSE and bCTUboundary is FALSE, the following applies:

pSelDsY[ idx ] = ( pY[ 0 ][ −2 ] + pY[ 0 ][ −1 ] + 1 ) >> 1 (8-189)

-otherwise (availTL is FALSE and bCTUboundary is TRUE), the following applies:

pSelDsY[ idx ] = pY[ 0 ][ −1 ] (8-190)

6.When cntT+ cntL is not equal to 0, the variables minY, maxY, minC and maxC are obtained as follows:

-

-when cntT+cntL is 2, set pSelComp[3] to pSelComp[0], pSelComp[2] to pSelComp[1], pSelComp[0] to pSelComp[1] and pSelComp[1] to pSelComp[3] with Comp replaced by DsY and C.

-arrays minGrpIdx[] and maxGrpIdx[] are set as: minGrpIdx[0] = 0, minGrpIdx[1] = 1, maxGrpIdx[0] = 2, maxGrpIdx[1] = 3.

-if pSelDsY[minGrpIdx[0]] > pSelDsY[minGrpIdx[1]], change (minGrpIdx[0], minGrpIdx[1]).

-if pSelDsY[maxGrpIdx[0]] > pSelDsY[maxGrpIdx[1]], change (maxGrpIdx[0], maxGrpIdx[1]).

-if pSelDsY[minGrpIdx[0]] >pSelDsY[maxGrpIdx[1]], change (minGrpIdx, maxGrpIdx ).

-if pSelDsY[minGrpIdx[1]] > pSelDsY[maxGrpIdx[0]], change (minGrpIdx[1], maxGrpIdx[0]).

-maxY = ( pSelDsY[maxGrpIdx[0]] + pSelDsY[maxGrpIdx[1]] + 1 ) >> 1.

-maxC = ( pSelC[maxGrpIdx[0]] + pSelC[maxGrpIdx[1]] + 1 ) >> 1.

-minY = ( pSelDsY[minGrpIdx[0]] + pSelDsY[minGrpIdx[1]] + 1 ) >> 1.

-minC = ( pSelC[minGrpIdx[0]] + pSelC[minGrpIdx[1]] + 1 ) >> 1.

7.variables a, b and k are obtained as follows:

-if numSampL is 0 and numSampT is 0, the following applies:

k = 0 (8-208) a = 0 (8-209) b = 1 << ( BitDepthC − 1) (8-210)

-otherwise, the following applies:

diff = maxY − minY (8-211)

-if diff is not 0, the following applies:

diffC = maxC − minC (8-212) x = Floor( Log2( diff ) ) (8-213) normDiff = ( ( diff << 4 ) >> x ) & 15 (8-214) x += (normDiff != 0) ? 10 (8-215) y = Floor( Log2( Abs ( diffC ) ) ) + 1 (8-216) a = ( diffC * ( divSigTable[ normDiff ] | 8 ) + 2y − 1 ) >> y (8-217) k = ( ( 3 + x − y ) < 1 ) ? 1 : 3 + x − y (8-218) a = ( ( 3 + x − y ) < 1 ) ? Sign( a ) * 15 : a (8-219) b = minC − ( ( a * minY ) >> k ) (8-220)

where divSigTable[ ] is defined as follows:

divSigTable[ ] = { 0, 7, 6, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 1, 1, 0 } (8-221)

-otherwise (diff equals 0), the following applies:

k = 0 (8-222) a = 0 (8-223) b = minC (8-224)

8. Prediction samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0.. nTbH − 1 are obtained as follows:

predSamples[ x ][ y ] = Clip1C( ( ( pDsY[ x ][ y ] * a ) >> k ) + b ) (8-225)

3.8 Alternative working design for CCLM's proposed prediction

This section describes an alternative exemplary embodiment that shows other modifications that may be made to the current working draft of the VVC standard. The equation numbers here refer to the corresponding equation numbers in the VVC standard.

Specification of INTRA_LT_CCLM, INTRA_L_CCLM and INTRA_T_CCLM intra prediction mode

...

The number of available neighboring chroma samples on the top and top right numTopSamp and the number of available neighboring chroma samples on the left and bottom left nLeftSamp are obtained as follows:

- if predModeIntra is equal to INTRA_LT_CCLM, the following applies:

numSampT = availT ? nTbW: 0 (8-157) numSampL = availL ? nTbH: 0 (8-158)

-otherwise, the following applies:

numSampT = ( availT && predModeIntra = = INTRA_T_CCLM ) ?

(nTbW + Min( numTopRight, nTbH )) : 0 (8-159)

numSampL = ( availL && predModeIntra = = INTRA_L_CCLM ) ?

(nTbH + Min( numLeftBelow, nTbW )) : 0 (8-160)

The bCTUboundary variable is obtained as follows:

bCTUboundary = (yTbC & (1 << (CtbLog2SizeY − 1) − 1) = = 0) ? TRUE: FALSE. (8-161)

The variable cntN and the array pickPosN[] with N replaced by L and T are obtained as follows:

-variable numIs4N is set to (( availT && availL && predModeIntra == INTRA_LT_CCLM ) ? 0 : 1).

-variable startPosN is set to numSampN >> ( 2 + numIs4N ).

-variable pickStepN is set to Max( 1, numSampN >> ( 1 + numIs4N )).

-if availN is TRUE and predModeIntra is INTRA_LT_CCLM or INTRA_N_CCLM, cntN is set to Min( numSampN, ( 1 + numIs4N ) << 1 ) and pickPosN[ pos ] is set to (startPosN + pos * pickStepN), with pos = 0..( cntN – 1 ).

-otherwise, cntN is set to 0.

Prediction samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH − 1 are obtained as follows:

-if both numSampL and numSampT are 0, the following will apply:

predSamples[ x ][ y ] = 1 << ( BitDepthC − 1) (8-162)

-otherwise, the following ordered steps apply:

1.Co-located brightness samples pY[ x ][ y ] with x = 0..nTbW * 2 − 1, y= 0..nTbH * 2 − 1 are set equal to the reconstructed brightness samples before performing the deblocking filtering process on locations ( xTbY + x, yTbY + y ).

2. Neighboring brightness samples pY[ x ][ y ] are obtained as follows:

-when numSampL is greater than 0, adjacent left luminance samples pY[ x ][ y ] with x = −1..−3, y = 0..2 * numSampL – 1 are set equal to the reconstructed luminance samples before performing the deblocking filtering process on locations ( xTbY + x, yTbY +y).

-when numSampT is greater than 0, adjacent top luminance samples pY[ x ][ y ] with x = 0..2 * numSampT − 1, y = −1, −2, are set equal to the reconstructed luminance samples before performing the deblocking filtering process on locations ( xTbY+ x, yTbY + y).

-when availTL is TRUE, the adjacent upper left luminance samples pY[ x ][ y ] with x = −1, y = −1, −2 are set equal to the reconstructed luminance samples before performing the deblocking filtering process on locations ( xTbY+ x, yTbY + y ).

3. Adjacent brightness samples after downsampling pDsY[ x ][ y ] with x = 0..nTbW − 1, y = 0..nTbH − 1 are obtained as follows:

-if sps_cclm_colocated_chroma_flag is 1, the following applies:

pDsY[ x ][ y ] with x = 1..nTbW − 1, y = 1..nTbH − 1 is obtained as follows:

pDsY[x][y]=(pY[2*x][2*y−1] +
pY[ 2 * x − 1][2 * y] + 4 * pY[2 * x][2 * y] + pY[2*x + 1][ 2 * y] + pY[ 2* x][2 *y + 1] + 4) >> 3 (8-163)

-if availL is TRUE, pDsY[ 0 ][ y ] with y = 1..nTbH − 1 is obtained as follows:

pDsY[0][y]=(pY[0][2*y−1] +
pY[ −1][ 2 * y ]+ 4 * pY[0][2 * y] + pY[1][2*y] + pY[0][2* y + 1] + 4) >> 3 (8-164)

-otherwise, pDsY[ 0 ][ y ] with y = 1..nTbH − 1 is obtained as follows:

pDsY[0][y] = (pY[0][2*y − 1] + 2*pY[0][2*y] + pY[0][2*y +1] + 2) >> 2 (8-165)

-if availT is TRUE, pDsY[ x ][ 0 ] with x = 1..nTbW − 1 is obtained as follows:

pDsY[x][0]=(pY[2*x][−1] +
pY[2*x − 1][0] + 4*pY[2* x][0] + pY[2* x + 1][0] + pY[2*x][1] + 4) >> 3 (8-166)

-otherwise, pDsY[ x ][ 0 ] with x = 1..nTbW − 1 is obtained as follows:

pDsY[ x ][0] = (pY[2*x − 1][0] + 2*pY[2* x][0] + pY[2 * x + 1][0] + 2 ) >> 2 (8-167)

-if availL is TRUE and availT is TRUE, pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[0][0]=(pY[0][−1] +
pY[−1][0]+4*pY[0][0]+pY[1][0] + pY[0][1] + 4) >> 3 (8-168)

-otherwise, if availL is TRUE and availT is FALSE, pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[0][0] = (pY[−1][0] + 2 * pY[0][0] + pY[1][0] + 2) >> 2 (8-169)

-otherwise, if availL is FALSE and availT is TRUE, pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[0][0] = (pY[0][ −1] + 2* pY[0][0] + pY[0][1] + 2) >> 2 (8-170)

-otherwise (availL is FALSE and availT is FALSE), pDsY[ 0 ][ 0 ] is obtained as follows:

pDsY[0][0] = pY[0][0] (8-171)

-otherwise, the following applies:

pDsY[ x ][ y ] with x = 1..nTbW − 1, y = 0..nTbH − 1 is obtained as follows:

pDsY[x][y] = (pY[2*x − 1][2* y] +pY[2*x − 1][2*y + 1] +
2* pY[2*x][2*y] + 2*pY[2* x][2*y + 1] + pY[2* x + 1][2* y] + pY[2*x + 1][2*y + 1] + 4) >> 3 (8-172)

-if availL is TRUE, pDsY[ 0 ][ y ] with y = 0..nTbH − 1 is obtained as follows:

pDsY[0][y] = (pY[−1][2*y]+ pY[−1][2*y+1] +
2*pY[0][2*y]+2*pY[0][ 2*y +1] + pY[1][2*y] + pY[1][2*y + 1] + 4) >>3 (8-173)

-otherwise, pDsY[ 0 ][ y ] with y = 0..nTbH − 1 is obtained as follows:

pDsY[ 0 ][ y ] = ( pY[ 0 ][ 2 * y ] + pY[ 0 ][ 2 * y + 1 ] + 1 ) >> 1 (8-174)

4. When numSampL is greater than 0, the selected neighboring left chroma samples pSelC[idx] are set to p[ -1 ][ pickPosL[ idx ]] with idx = 0..(cntL – 1), and the selected neighboring left luminance samples after downsampling pSelDsY[ idx ] with idx = 0..(cntL-1) are obtained as follows:

-variable y is set equal to pickPosL[ idx ].

-if sps_cclm_colocated_chroma_flag is 1, the following applies:

-if y > 0 || availTL == TRUE,

pSelDsY[idx]=(pY[−2][2*y−1] +
pY[−3][2*y]+4*pY[−2][2*y]+pY[−1][2*y] + pY[ −2][2*y + 1] + 4 ) >>3 (8-175)

- otherwise,

pSelDsY[ idx ] = ( pY[ −3 ][ 0 ] + 2 * pY[ −2 ][ 0 ] + pY[ −1 ][ 0 ] + 2 ) >> 2 (8-177)

-otherwise, the following applies:

pSelDsY[idx] = (pY[−1][2*y]+pY[−1][2*y+1] +
2*pY[−2][2* y] + 2*pY[−2][2* y + 1] + pY[−3][2*y] + pY[−3][2*y + 1 ] + 4) >> 3 (8-178)

5. When numSampT is greater than 0, the selected neighboring top chrominance samples pSelC[ idx ] are set to p[ pickPosT[ idx – cntL ]][ -1 ] with idx = cntL..( cntL + cntT – 1 ), and the neighboring top luminance samples after downsampling pSelDsY[ idx ] with idx = cntL..( cntL + cntT – 1) are specified as follows:

-variable x is set to pickPosT[ idx – cntL ].

-if sps_cclm_colocated_chroma_flag is 1, the following applies:

-if x > 0:

-if bCTUboundary is FALSE, the following applies:

pSelDsY[idx]=(pY[2*x][−3] +
pY[2*x −1][ −2] + 4*pY[2* x][ −2] + pY[2*x + 1][−2] + pY[2* x][−1] + 4) >> 3 (8-179)

-otherwise, (bCTUboundary is TRUE), the following applies:

pSelDsY[idx]=(pY[2*x−1][−1] +
2* pY[ 2 * x ][ −1] + pY[ 2 * x + 1][ −1] + 2) >> 2 (8-180)

-otherwise:

-if availTL is TRUE and bCTUboundary is FALSE, the following applies:

pSelDsY[idx]=(pY[0][−3] +
pY[ −1][ −2] + 4 * pY[0][ −2] + pY[1][ −2] + pY[0][ −1] + 4) >> 3 (8-181)

-else, if availTL is TRUE and bCTUboundary is TRUE, the following applies:

pSelDsY[idx]=(pY[−1][−1] +
2* pY[0][ −1] + pY[1][ −1] + 2) >> 2 (8-182)

-else, if availTL is FALSE and bCTUboundary is FALSE, the following applies:

pSelDsY[idx] = (pY[0][−3] + 2 * pY[0][ −2] + pY[0][ −1] + 2) >> 2 (8-183)

-otherwise (availTL is FALSE and bCTUboundary is TRUE), the following applies:

pSelDsY[ idx ] = pY[ 0 ][ −1 ] (8-184)

-otherwise, the following applies:

-if x > 0:

-if bCTUboundary is FALSE, the following applies:

pSelDsY[idx]=(pY[2*x−1][−2]+pY[2*x−1][−1] +
2*pY[2*x][−2] +2*pY[2*x][ −1] +pY[2*x + 1][−2] + pY[2*x + 1][ −1 ] +4) >> 3 (8-185)

-otherwise, (bCTUboundary is TRUE), the following applies:

pSelDsY[idx]=(pY[2*x−1][−1] +
2*pY[2* x][ −1] + pY[2* x + 1][ −1] + 2) >> 2 (8-186)

-otherwise:

-if availTL is TRUE and bCTUboundary is FALSE, the following applies:

pSelDsY[idx]=(pY[−1][−2]+pY[−1][−1] +
2*pY[0][−2] + 2*pY[0][ −1] + pY[1][ −2] + pY[1][ −1] + 4) >> 3 (8-187)

-else, if availTL is TRUE and bCTUboundary is TRUE, the following applies:

pSelDsY[idx]=(pY[−1][−1] +
2* pY[0][ −1] + pY[1][ −1] + 2) >> 2 (8-188)

-else, if availTL is FALSE and bCTUboundary is FALSE, the following applies:

pSelDsY[ idx ] = ( pY[ 0 ][ −2 ] + pY[ 0 ][ −1 ] + 1 ) >> 1 (8-189)

-otherwise, (availTL is FALSE and bCTUboundary is TRUE), the following applies:

pSelDsY[ idx ] = pY[ 0 ][ −1 ] (8-190)

6.When cntT+ cntL is not equal to 0, the variables minY, maxY, minC and maxC are obtained as below:

-

-when cntT+cntL is 2, set pSelComp[3] equal to pSelComp[0], pSelComp[2] equal to pSelComp[1], pSelComp[0] equal to pSelComp[1] and pSelComp[1] equal to pSelComp[3] with Comp replaced by DsY and C.

-arrays minGrpIdx[] and maxGrpIdx[] are set as: minGrpIdx[0] = 0, minGrpIdx[1] = 2, maxGrpIdx[0] = 1, maxGrpIdx[1] = 3.

-if pSelDsY[minGrpIdx[0]] > pSelDsY[minGrpIdx[1]], Swap(minGrpIdx[0], minGrpIdx[1]).

-if pSelDsY[maxGrpIdx[0]] > pSelDsY[maxGrpIdx[1]], Swap(maxGrpIdx[0], maxGrpIdx[1]).

-if pSelDsY[minGrpIdx[0]] > pSelDsY[maxGrpIdx[1]], Swap(minGrpIdx, maxGrpIdx ).

-if pSelDsY[minGrpIdx[1]] > pSelDsY[maxGrpIdx[0]], Swap(minGrpIdx[1], maxGrpIdx[0]).

-maxY = ( pSelDsY[maxGrpIdx[0]] + pSelDsY[maxGrpIdx[1]] + 1 ) >> 1.

-maxC = ( pSelC[maxGrpIdx[0]] + pSelC[maxGrpIdx[1]] + 1 ) >> 1.

-minY = ( pSelDsY[minGrpIdx[0]] + pSelDsY[minGrpIdx[1]] + 1 ) >> 1.

-minC = ( pSelC[minGrpIdx[0]] + pSelC[minGrpIdx[1]] + 1 ) >> 1.

7.Variables a, b and k are obtained as follows:

-if numSampL is 0 and numSampT is 0, the following applies:

k = 0 (8-208) a = 0 (8-209) b = 1 << ( BitDepthC − 1) (8-210)

-otherwise, the following applies:

diff = maxY − minY (8-211)

-if diff is not 0, the following applies:

diffC = maxC − minC (8-212) x = Floor( Log2( diff ) ) (8-213) normDiff = ( ( diff << 4 ) >> x ) & 15 (8-214) x += (normDiff != 0) ? 10 (8-215) y = Floor( Log2( Abs ( diffC ) ) ) + 1 (8-216) a = ( diffC * ( divSigTable[ normDiff ] | 8 ) + 2y − 1 ) >> y (8-217) k = ( ( 3 + x − y ) < 1 ) ? 1 : 3 + x − y (8-218) a = ( ( 3 + x − y ) < 1 ) ? Sign( a ) * 15 : a (8-219) b = minC − ( ( a * minY ) >> k ) (8-220)

when divSigTable[ ] is specified as:

divSigTable[ ] = { 0, 7, 6, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 1, 1, 0 } (8-221)

-otherwise, (diff is 0), the following applies:

k = 0 (8-222) a = 0 (8-223) b = minC (8-224)

8. Prediction samples predSamples[ x ][ y ] with x = 0..nTbW − 1, y = 0.. nTbH − 1 are obtained as follows:

predSamples[ x ][ y ] = Clip1C( ( ( pDsY[ x ][ y ] * a ) >> k ) + b ) (8-225)

The above examples may be added to the context of the methods described below, for example, methods 1800, 1900, and 2000, which may be implemented in a video encoder and/or decoder.

FIG. 18A shows a flowchart of an exemplary method for video processing. Method 1820 includes determining step 1822, for converting between the current video block, which is a chrominance block, and the encoded video representation, cross-component linear model (CCLM) prediction mode parameters based on chroma samples that are selected based on the W available top neighbor samples. , W is an integer. Method 1810 further includes the step 1814 of performing a conversion based on the determination.

FIG. 18B shows a flow diagram of an exemplary method for video processing. Method 1820 includes determining step 1822 for converting between the current video block, which is a chroma block, and the encoded video representation, cross-component linear model (CCLM) prediction mode parameters based on chroma samples that are selected based on H available left neighbor samples. current video block. Method 1820 further includes the step 1824 of performing a conversion based on the determination.

FIG. 19A shows a flowchart of an exemplary method for video processing. Method 1910 includes a step 1912 of determining, to transform between the current video block, which is a chrominance block, and the encoded video representation, cross-component linear model (CCLM) parameters based on two or four chroma samples and/or corresponding luma samples. Method 1910 further includes the step 1914 of performing a conversion based on the determination.

FIG. 19B shows a flowchart of an exemplary method for video processing. Method 1920 includes a selection step 1922 for converting between the current video block, which is a chroma block, and a coded representation of the video, chrominance samples based on a position rule, the chrominance samples used to obtain the cross-component linear model (CCLM) parameters. Method 1920 further includes the step 1924 of performing a conversion based on the determination. In this example, the position rule specifies to select chroma samples that are located within the top row and/or left column of the current video block.

FIG. 20A shows a flowchart of an exemplary method for video processing. Method 2010 includes determining step 2012, for converting between a current video block, which is a chroma block, and a coded representation of the video, positions at which luminance samples are downsampled, wherein the luminance samples after downsampling are used to determine intercomponent linear parameters model (CCLM) based on the chrominance samples and the downsampled luminance samples, in which the downsampled luminance samples are at positions corresponding to the positions of the chrominance samples that are used to obtain the CCLM parameters. The method 2010 further includes the step 2014 of performing a conversion based on the determination.

FIG. 20B shows a flowchart of an exemplary method for video processing. Method 2020 includes determining step 2022, for converting between a current video block, which is a chroma block, and an encoded representation of the video, a method for deriving cross-component linear model (CCLM) parameters using chroma samples and luma samples, based on the encoding state. associated with the current video block. Method 2020 further includes the step 2024 of performing a conversion based on the determination.

FIG. 20C shows a flowchart of an exemplary method for video processing. Method 2030 includes determining step 2032, for converting between the current video block, which is a chrominance block, and the encoded video representation, whether to obtain maximum values and/or minimum values of the luma component and the chrominance component that are used to obtain the intercomponent linear parameters. model (CCLM) based on the accessibility of the left neighbor block and the top neighbor block of the current video block. Method 2030 further includes the step 2034 of performing a conversion based on the determination.

4 Example implementations of the presented technology

FIG. 21A is a block diagram of an apparatus 3000. The apparatus 3000 may be used to implement one or more of the methods described herein. The device 3000 may be embodied in a smartphone, tablet, computer, Internet of Things (IoT) receiver, etc. Device 3000 may include one or more processors 3002, one or more memories 3004, and video processing circuitry 3006. The processor(s) 3002 may be configured to implement one or more of the methods (including, but not limited to, methods as shown in FIGS. 18-29C) described herein. Memory(s) 3004 may be used to store data and code used to implement the methods and technologies described herein. Video processing circuitry 3006 may be used to implement, in hardware circuit form, some of the technologies described herein.

FIG. 21B is another example of a block diagram of a video processing system in which the disclosed technologies may be implemented. FIG. 30B is a block diagram showing an exemplary video processing system 3100 in which various methods disclosed herein may be implemented. Various implementations may include some or all of the components of the system 3100. The system 3100 may include an input 3102 for receiving video content. The video content may be received in a raw or uncompressed format, such as 8 or 10 bit multi-component pixel values, or may be received in a compressed or encoded format. Input 3102 may represent a network interface, a peripheral bus interface, or a storage interface. Examples of a network interface include wired interfaces such as Ethernet, passive optical network (PON), etc., and wireless interfaces such as Wi-Fi or cellular interfaces.

System 3100 may include an encoding component 3104 that may implement various encoding or encryption methods described herein. The encoding component 3104 may reduce the average bit rate of the video from the input 3102 to the output of the encoding component 3104 to obtain an encoded representation of the video. Therefore, encoding technologies are sometimes called video compression technologies or video transcoding technologies. The output of encoding component 3104 may be either stored or transmitted via a communication connected as represented by component 3106. The stored or reported video representation bitstream (or encoded) received at input 3102 may be used by component 3108 to generate pixel values or display video , which is sent to display interface 3110. The process of generating video for user viewing from a bitstream representation is sometimes called video decompression. Additionally, while some video processing operations are called "encoding" operations or tools, it is apparent that the encoding tools or operations are used in the encoder and the corresponding decoding tools or operations, which are the inverse of the encoding that would be performed by the decoder.

Examples of a peripheral bus interface or display interface may include Universal Serial Bus (USB) or High Definition Multimedia Interface (HDMI) or DisplayPort and so on. Examples of storage interfaces include SATA (Serial Advanced Attachment Technology), PCI, IDE, and the like. The technologies described herein may be implemented in various electronic devices, such as mobile phones, laptops, smartphones, or other devices that are capable of performing digital data and/or video processing.

In some embodiments, video encoding methods may be implemented using a device that is implemented on a hardware platform, as described with reference to FIG. 21A or FIG. 21B.

Various technologies preferably included in the embodiments may be described using the following format based on the clauses.

The first set of paragraphs describes specific features and aspects of the described technologies listed in the preceding section, including, for example, Examples 16 and 17.

1. A video processing method, comprising: determining, for conversion between a current video block, which is a chrominance block, and an encoded video representation, intercomponent linear model prediction mode parameters based on chrominance samples that are selected based on W available top neighboring samples, W being integer; and performing a conversion based on the definition.

2. The method of 1, wherein the CCLM prediction mode uses the linear mode to obtain prediction values of a chrominance component from another component.

3. Method according to 1, in which W is set to i) the width of the current video block, ii) L times the width of the current video block, L being an integer, iii) the sum of the height of the current video block and the width of the current video block, or iv) the sum of the width of the current video block and the number of available top-right adjacent samples.

4. The method of 1, wherein W depends on the availability of at least one of the upper adjacent block or the left adjacent block of the current video block.

5. Method according to 1, in which W depends on the encoding mode of the current video block.

6. Method according to 3, in which L is valued depending on the availability of the top right block or the top left sample that is located next to the current video block.

7. The method of 1, wherein the chroma samples are selected based on a first position offset value (F) and a step value (S) that depend on W.

8. The method of 7, in which the top left sample has a coordinate (x0, y0), and the selected chrominance samples have coordinates (x0 + F + K × S, y0-1), K is an integer between 0 and kMax.

9. Method according to 7, in which F = W/P or F = W/P + offset, P is an integer.

10. Method according to 9, in which F = W >> (2 + numIs4T), in which numIs4T is equal to 1 in case of four adjacent samples selected within the top adjacent row and, otherwise, numIs4T is equal to 0, in which the symbol >> means arithmetic right shift.

11. Method according to 6, in which S = W Q, Q is an integer.

12. Method according to 6, in which S is not less than 1.

13. Method according to 11 or 12, in which S = Max (1, W >> (1 + numIs4T)), in which numIs4T is equal to 1 in the case of four adjacent samples selected within the upper adjacent row and, otherwise, numIs4T is equal to 0 , in which the symbol >> means an arithmetic shift to the right.

14. The method of 10 or 13, wherein numIs4T is equal to 1 in the case where top adjacent samples are available, left adjacent samples are available, and the current video block is encoded by a normal CCLM, which is different from the first CCLM using only left adjacent samples, and different from the second CCLM using only the top neighboring samples.

15. Method according to 7, in which F = S/R, R is an integer.

16. Method according to 7, in which S = F/Z, Z is an integer.

17. The method as in any one of 8-16, wherein at least one of Kmax, F, S or offset depends on the prediction mode of the current video block, which is one of the first CCLM using only left adjacent samples, the second CCLM with using only the top neighbor samples, normal CCLM using both left neighbor and top neighbor samples, or other modes other than first CCLM, second CCLM, and normal CCLM.

18. The method as in any one of 8-16, wherein at least one of Kmax, F, S or offset depends on the width and/or height of the current video block.

19. The method as in any one of 8-16, wherein at least one of Kmax, F, S, or offset depends on the availability of adjacent samples.

20. The method according to any one of 8-16, in which at least one of Kmax, F, S or offset depends on W.

21. A video processing method, comprising: determining, for transforming between a current video block, which is a chrominance block, and an encoded video representation, cross-component linear model (CCLM) prediction mode parameters based on chroma samples that are selected based on H availability of left neighbors samples of the current video block; and performing a conversion based on the definition.

22. The method of 21, wherein the CCLM prediction mode uses the linear mode to obtain prediction values of a chrominance component from another component.

23. The method of 21, wherein H is set to one of i) the height of the current video block, ii) L times the height of the current video block, L being an integer, iii) the sum of the height of the current video block and the width of the current video block, or iv) the sum the height of the current video block and the number of available bottom-left adjacent samples.

24. The method of 21, wherein H depends on the availability of at least one of the upper adjacent block or the left adjacent block of the current video block.

25. Method according to 21, in which H depends on the encoding mode of the current video block.

26. The method of 23, wherein L has a value depending on the availability of a lower left block or a lower left sample that is adjacent to the current video block.

27. The method of 21, wherein the chroma samples are selected based on a first position offset value (F) and a step value (S) that depend on H.

28. The method of 27, wherein the top left sample has a coordinate (x0, y0) and the selected chroma samples have coordinates (x0-1, y0 + F + K × S), K is an integer between 0 and kMax.

29. The method according to 27, in which F = H/P or F = H/P + offset, P is an integer.

30. The method of 29, in which F = H >> (2 + numIs4L), in which numIs4L is equal to 1 in the case of four selected adjacent samples in the left adjacent column; otherwise equal to 0.

31. Method according to 27, in which S = H/Q, Q is an integer.

32. Method according to 27, in which S is equal to at least 1.

33. The method of 31 or 32, in which s = max (1, H >> (1 + numIs4L)), in which numIs4L is 1 if there are four selected adjacent samples in the left adjacent column and otherwise, numIs4L is 0 .

34. The method of 30 or 33, wherein numIs4L is equal to 1 if top neighbor samples are available, left neighbor samples are available, and the current video block is encoded by a normal CCLM that is different from the first CCLM using only left neighbor samples and different from the second CCLM using only top neighboring samples.

35. Method according to 27, in which F = S R, R is an integer.

36. Method according to 27, in which S = F/Z, Z is an integer.

37. The method as in any one of 28-36, wherein at least one of Kmax, F, S or offset depends on the prediction mode of the current video block, which is one of the first CCLM using only left adjacent samples, the second CCLM with using only the top neighbor samples, a third CCLM using both the left neighbor and top neighbor samples, or other modes other than the first CCLM, second CCLM, and third CCLM.

38. The method as in any one of 28-36, wherein at least one of Kmax, F, S or offset depends on the width and/or height of the current video block.

39. The method according to any one of 28-36, in which at least one of Kmax, F, S or offset depends on H.

40. The method as in any one of 28-36, wherein at least one of Kmax, F, S, or offset depends on the availability of neighboring samples.

41. The method of 21, wherein H is set to the sum of the height of the current video block and the width of the current video block if the top right adjacent block of the current video block is available.

42. The method of 21, wherein in the case where left neighboring samples are not available, the selected chroma samples have height H regardless of whether the current video block has a first CCLM using only the top neighboring samples or not.

43. Method according to 1, in which W is set to the sum of the height of the current video block and the width of the current video block in the case of a lower left adjacent block of the current video block.

44. The method of 1, wherein in the case of unavailability of the top neighboring samples, the selected chroma samples are numbered W, regardless of whether the current video block has a first CCLM using only the left neighboring samples or not.

45. The method as in any one of 1-44, wherein performing the transformation includes generating an encoded representation from the current block.

46. The method as in any one of 1-44, wherein performing the transformation includes generating a current block from the encoded representation.

47. An apparatus in a video system comprising a processor and a read-only instruction memory, wherein the instructions, when executed by the processor, cause the processor to execute the method of any one of 1-46.

48. A computer program product stored on a non-transitory computer readable medium, the computer program product includes program code for performing the method of any one of 1-46.

The tenth set of paragraphs describes specific features and aspects of the disclosed technologies listed in the preceding section, including, for example, Examples 18 and 19.

1. A video processing method, comprising: determining, to transform between a current video block, which is a chrominance block, and an encoded video representation, cross-component linear model (CCLM) parameters based on two or four chroma samples and/or corresponding luminance samples; and performing a conversion based on the definition.

2. The method of 1, wherein the corresponding luminance samples are obtained by downsampling.

3. Method according to 1, in which MaxY/MaxC and MinY/MinC are obtained first and are used to obtain parameters.

4. Method according to 3, in which the parameters are obtained based on the 2-point approach.

5. The method of 3, wherein two chroma samples are selected to obtain MaxY/MaxC and MinY/MinC, and wherein MinY is set to the smaller luminance sample value, MinC is its corresponding chroma sample value, MaxY is set to the largest luminance sample value, and MaxC is its corresponding chroma sample value.

6. Method according to 3, in which four chroma samples are selected to obtain MaxY/MaxC and MinY/MinC and, in which the four chroma samples and corresponding luma samples are divided into two arrays G0 and G1, each array including two chroma samples and their corresponding brightness samples.

7. Method according to 6, in which the two arrays G0 and G1 include one of the following sets:

i) G0 = {S0, S1}, G1 = {S2, S3},

ii) G0 = {S1, S0}, G1 = {S3, S2},

iii) G0 = {S0, S2}, G1 = {S1, S3},

iv) G0 = {S2, S0}, G1 = {S3, S1},

v) G0 = {S1, S2}, G1 = {S0, S3},

vi) G0 = {S2, S1}, G1 = {S3, S0},

vii) G0 = {S0, S3}, G1 = {S1, S2},

viii) G0 = {S3, S0}, G1 = {S2, S1},

ix) G0 = {S1, S3}, G1 = {S0, S2},

x) G0 = {S3, S1}, G1 = {S2, S0},

xi) G0 = {S3, S2}, G1 = {S0, S1} or

xii) G0 = {S2, S3}, G1 = {S1, S0} and

where S0, S1, S2, S3 include four chrominance samples, respectively, and further include corresponding luma samples, respectively.

8. The method of 7, wherein when comparing two luminance sample values G0[0] and G0[1], the chrominance sample and its corresponding luminance sample in G0[0] are replaced with the same in G0[1].

9. The method of 8, wherein the chrominance sample and its corresponding luma sample G0[0] are replaced by the same G0[1] in the case where the luma sample value G0[0] is greater than the luma sample value G0[1].

10. The method of 7, wherein when comparing two luma sample values G1[0] and G1[1], the chrominance sample and its corresponding luma sample in G1[0] are replaced by the same G1[1].

11. The method of 10, wherein the chrominance sample and its corresponding luma sample G1[0] are replaced by the same G1[1] in the case where the luma sample value G1[0] is greater than the luma sample value G1[1].

12. Method according to 6, in which, when comparing two luminance sample values G0[0] and G1[1], the chrominance samples and their corresponding luminance samples G0[0] or G0[1] are replaced by the same G1[0] or G1 [1].

13. The method of 12, wherein the chrominance samples and their corresponding luminance samples G0[0] are replaced by the same G1[0] in the case where the luminance sample value G0[0] is greater than the luminance sample value G1[1].

14. The method of 7, in which when comparing two luminance sample values G0[1] and G1[0], the chrominance sample and its corresponding luminance sample G0[1] are replaced by the same G1[0].

15. The method as in 14, wherein the chrominance sample and its corresponding luma sample G0[1] are replaced by the same G1[0] in the case where the luma sample value G0[1] is greater than the luma sample value G1[0].

16. The method of 7, wherein when comparing two luminance sample values G0[0], G0[1], G1[0] and G1[1], subsequent replacement operations are carried out in the order: i) replacement operation of the chrominance sample and its corresponding luminance samples G0 [0] with the same ones from G0 [1], ii) the operation of replacing the chroma samples and their corresponding luminance samples G1 [0] with the same G1 [1], iii) the operation of replacing the chrominance samples and their corresponding luminance samples G0 [0] with the same G1[0] and iv) the operation of replacing the chrominance sample and its corresponding luma sample G0[1] with the same G1[0].

17. The method of 7 or 16, wherein maxY is calculated from the sum of the luminance sample values of G1[0] and G1[1], and maxC is calculated from the sum of the chrominance sample values of G1[0] and G1[1].

18. The method of 7 or 16, wherein maxY is calculated based on the average of the luma sample values of G1[0] and G1[1], and maxC is calculated based on the average of the chroma sample values of G1[0] and G1[1].

19. The method of 7 or 16, wherein minY is calculated as the sum of the luma sample values G0[0] and G0[1], and minC is calculated based on the sum of the chrominance sample values G0[0] and G0[1].

20. The method of 7 or 16, wherein minY is calculated as the average of the luminance sample values G0[0] and G0[1] and minC is calculated based on the average of the chroma sample values G0[0] and G0[1].

21. The method of 17 or 20, which performs maxY and maxC calculations or minY and minC calculations after any of the replacement operations that are performed when comparing two luminance sample values G0[0], G0[1], G1[0] and G1 [1], in which the replacement operations include: i) the operation of replacing the chroma sample and its corresponding luma sample G1[0] with those in G1[1], ii) the operation of replacing the chroma samples and their corresponding luma samples G0[0 ] with the same ones from G1[0] and iii) the operation of replacing the chrominance sample and its corresponding luma sample G0[1] with the same one from G1[0] or iv) the operation of replacing the chroma sample and the corresponding luma samples G0[0] with those same in G0 [1].

22. The method of 1, wherein in the case of only two chroma samples, padding is performed on the two available chroma samples to provide four chroma samples and is also performed on the two corresponding available luma samples G0[0] to the same in G0[1].

23. The method of 22, wherein the four chrominance samples include two available chrominance samples and two fill chroma samples that are copied from the two available chroma samples, and the four corresponding luma samples include two available luma samples and two fill luma samples that copied from two available brightness samples.

24. The method of 7, wherein S0, S1, S2, S3 are chrominance samples and corresponding luma samples are selected in a predetermined order within the top row and/or left column of the current video block.

25. A video processing method, comprising: selecting, to transform between a current video block, which is a chrominance block, and a coded representation of the video, chrominance samples based on a position rule, the chroma samples being used to obtain the parameters of a cross-component linear model (CCLM); and performing the conversion based on the determination in which the position rule specifies to select chroma samples that are located within the top row and/or left column of the current video block.

26. The method of 25, wherein the top row and left column have W samples and H samples, respectively, W and H are the width and height of the current video block, respectively.

27. The method of 26, wherein the position rule is applied to the current block of video encoded in a normal CCLM mode, different from the first CCLM mode, which uses only the top adjacent samples to obtain parameters of the intercomponent linear model, and from the second CCLM mode, which uses only the left neighbors samples to obtain the parameters of the intercomponent linear model.

28. The method of 26, wherein the position rule specifies to select chroma samples that are located within the top row and top right row of the current video block.

29. The method of 28, wherein the top row and the top right row have W samples and H samples, respectively, W and H are the width and height of the current video block, respectively.

30. The method of 28, wherein only the available samples within the top row and the top right row are selected.

31. The method of 28, wherein the position rule is applied to the current block of video encoded with a first CCLM mode that uses only the top adjacent samples to obtain intercomponent linear model parameters.

32. The method of 28, wherein the position rule is applied to the case that the top row is available and the left column is not available, and that the current block of video is encoded in a normal CCLM mode, which is different from the first CCLM mode, which uses only the top adjacent samples to obtain CCLM parameters, and from the second CCLM mode, which uses only the left adjacent samples to obtain the parameters of the intercomponent linear model.

33. The method as in any one of 26 to 32, wherein numSampT is set based on a rule indicating that numSampT is set equal to nTbW in the case where upper adjacent samples are available, and numSampT is set equal to 0 in the case where upper neighboring samples are not available and, in where numSampT represents the number of chroma samples within the top adjacent row used to obtain the intercomponent linear model parameters, and nTbW represents the width of the current video block.

34. The method of 33, wherein the rule is applied to the current block of video encoded in a normal CCLM mode, which differs from the first CCLM mode, which uses only the top adjacent samples to obtain the CCLM, and from the second CCLM mode, which uses only the left adjacent samples to obtain the CCLM. obtaining the parameters of the intercomponent linear model.

35. The method as in any one of 26-32, wherein numSampT is set based on a rule indicating that numSampT is set equal to nTbW + Min( numTopRight, nTbH ) in case the top adjacent samples are available and the current video block is encoded by the first CCLM mode that uses only the top adjacent samples to obtain the interlinear model parameters and, otherwise, numSampT is set to 0 and, in which numSampT represents the number of chroma samples within the top adjacent row used to obtain the intercomponent linear model parameters, nTbW and nTbH represent the width and height of the current block, respectively, and numTopRight represents the number of available top-right neighboring samples.

36. Method according to 25 in which the position rule specifies to select chroma samples that are located in the left column and in the lower left column of the current video block.

37. The method of 36, and wherein the left column and the lower left column have H samples and W samples, respectively, W and H are the width and height of the current video block, respectively.

38. Method as in 36, which selects only the available samples in the left column and lower left column.

39. The method of 36, wherein the position rule is applied to the current block of video encoded with a second CCLM mode that uses only left adjacent samples to obtain intercomponent linear model parameters.

40. The method of 36, wherein the position rule is applied to the case that the top row is not available and the left column is available and that the current video block is encoded in a normal CCLM mode, which is different from the first CCLM mode, which uses only the top adjacent samples to obtain the CCLM, and from the second CCLM mode, which uses only left neighbor samples to obtain the parameters of the intercomponent linear model.

41. The method as in any one of 36-40, wherein numSampL is set based on a rule indicating that numSampL is set equal to nTbH in case left adjacent samples are available and, otherwise, numSampL is set equal to 0 and, wherein numSampL represents the number chrominance samples in the left adjacent column used to obtain the intercomponent linear model parameters, and nTbH represents the height of the current video block.

42. The method of 41, wherein the rule is applied to a current block of video encoded in a normal CCLM mode, which differs from the first CCLM mode, which uses only the top adjacent samples to obtain intercomponent linear model parameters, and from the second CCLM mode, which uses only the left ones adjacent samples to obtain the parameters of the between-component linear model.

43. The method as in any one of 36-40, wherein numSampL is set based on a rule indicating that numSampL is set equal to nTbH + Min( numLeftBelow, nTbW ) in the case where left adjacent samples are available and the current video block is encoded using the second CCLM mode , which uses only the left adjacent samples to obtain the between-linear model parameters and that otherwise, numSampL is set to 0, and in which numSampL represents the number of chroma samples in the left adjacent column used to obtain the between-linear model parameters, nTbW and nTbH represent the width and height of the current block, respectively, and numLeftBelow represents the number of available lower left neighboring samples.

44. The method of any one of 25-43, wherein luma samples corresponding to the selected chrominance samples are used to obtain parameters of the intercomponent linear model.

45. The method of 44, wherein the luminance samples are obtained by downsampling.

46. The method as in any one of 1-45, wherein performing the transformation includes generating an encoded representation from the current block.

47. The method as in any one of 1-45, wherein performing the transformation includes generating a current block from the encoded representation.

48. The method as in any one of 1-45, wherein CCLM uses co-located downsampled luminance component samples to obtain prediction values of the chrominance component samples of the current block based on a linear model including an intercomponent linear model.

49. An apparatus in a video system including a processor and a read-only instruction memory, wherein the instructions, when executed by the processor, cause the processor to execute the method of any one of 1-48.

50. A computer program product stored on a non-transitory computer readable medium, the computer program product includes program code for performing the method of any one of 1-48.

The third set of paragraphs describes specific features and aspects of the disclosed technologies listed in the preceding section, including, for example, Examples 20, 21, 22.

1. A video processing method, comprising: determining, for conversion between a current video block, which is a chrominance block, and a coded representation of the video, positions at which luminance samples are downsampled, wherein the luminance samples after downsampling are used to determine inter-component parameters a linear model (CCLM) based on the chrominance samples and the downsampled luminance samples, in which the downsampled luminance samples are at positions corresponding to the positions of the chrominance samples that are used to obtain the CCLM parameters; and performing a conversion based on the definition.

2. Method as in 1, in which the luminance samples are not downsampled to a position that is outside the current video block and is not used to determine the CCLM parameters.

3. A video processing method, comprising: defining, for transforming between a current video block, which is a chrominance block, and an encoded video representation, a method for deriving cross-component linear model (CCLM) parameters using chroma samples and luma samples based on the encoding state, associated with the current video block; and performing a conversion based on the definition.

4. Method according to 3, in which the encoding state corresponds to the color format of the current video block.

5. Method according to 4, in which the color format is 4:2:0 or 4:4:4.

6. Method according to 3, in which the encoding condition corresponds to the color representation method of the current video block.

7. The method of 6, wherein the color representation method is RGB or YCbCr.

8. The method of 3, wherein the chrominance samples are downsampled and the determination depends on the locations of the chrominance samples after downsampling.

9. The method of 3, wherein the parameter deriving method comprises determining CCLM parameters based on chroma samples and luma samples that are selected from a group of adjacent chroma samples based on a position rule.

10. The method of 3, wherein the method of obtaining the parameters comprises determining the CCLM parameters based on the maximum and minimum values of the chroma samples and the luma samples.

11. The method of 3, wherein the parameter deriving method comprises determining CCLM parameters that are entirely determined by two chroma samples and corresponding two luma samples.

12. The method of 3, wherein the parameter obtaining method comprises determining CCLM parameters using a parameter table whose entries are obtained in accordance with two chrominance sample values and two luma sample values.

13. A method for processing video, comprising: determining, for conversion between a current video block, which is a chrominance block, and an encoded video representation, whether to obtain the maximum values and/or minimum values of the luma component and the chrominance component used to obtain the intercomponent parameters linear model (CCLM), based on the availability of the left neighbor block and the top neighbor block of the current video block; and performing a conversion based on the definition.

14. The method of 13, wherein the maximum values and/or minimum values are not obtained if the left adjacent block and the upper adjacent block are not available.

15. The method of 13, wherein determining definitions based on the number of available neighboring samples of the current block of video, and wherein the available neighboring samples are used to obtain parameters of the intercomponent linear model.

16. The method of 15, wherein maximum values and/or minimum values are not obtained in the case of numSampL == 0 and numSampT == 0, numSampL and numSampT indicate the number of available adjacent samples from the left adjacent block and the number of available adjacent samples from the upper block, respectively, and wherein the available neighboring samples from the left neighboring block and the available neighboring samples from the upper neighboring block are used to obtain the parameters of the between-component linear model.

17. The method of 15, wherein the maximum values and/or minimum values are not obtained in the case of numSampL + numSampT == 0, numSampL and numSampT indicate the number of available adjacent samples from the left adjacent block and the number of available adjacent samples from the upper adjacent block, respectively, and wherein the available neighboring samples from the left neighboring block and the available neighboring samples from the upper neighboring block are used to obtain parameters of the between-component linear model.

18. The method as in any one of 1-17, wherein performing the transformation includes generating an encoded representation from the current block.

19. The method as in any one of 1-17, wherein performing the transformation includes generating a current block from the encoded representation.

20. An apparatus in a video system comprising a processor and a read-only instruction memory, wherein the instructions, when executed by the processor, cause the processor to execute the method of any one of 1-19.

21. A computer program product stored on a non-transitory computer readable medium, the computer program product includes program code for performing the method of any one of 1-19.

The fourth set of paragraphs describes specific features and aspects of the disclosed technologies listed in the previous section.

1. A video processing method, comprising: determining, for a current block that contains a chroma block and is based on two or more chroma samples, a set of linear model parameter values in which two or more chroma samples are selected from a group of adjacent chroma samples for the chroma block; and performing reconstruction based on the linear model of the current video block.

2. Method according to 1, in which the upper left sample of the chrominance block is equal to (x,y), in which the width and height of the chrominance block are equal to W and H, respectively, and in which the group of adjacent chroma samples contains:

Sample A with coordinates (x - 1, y),

Sample D with coordinates (x - 1, y + h - 1),

Sample J with coordinates (x, y - 1), and

Sample M with coordinates (x + w - 1, y - 1).

3. The method of 2, wherein the upper left adjacent block and the above-mentioned adjacent block of the current video block are available, and wherein two or more chrominance samples contain A, D, J and M samples.

4. The method of 2, wherein the upper left adjacent block of the current video block is available, and wherein two or more chrominance samples contain A and D samples.

5. Method according to 2, in which the upper adjacent block of the current video block is available, and in which two or more chrominance samples contain J and M samples.

6. A method for processing video, comprising: generating for the current video block, which contains a chrominance block, a plurality of groups containing chrominance and brightness samples of an adjacent block of the current video block; determining, based on a variety of groups, maximum and minimum values, a set of values for the parameters of the linear model; determining, based on the maximum and minimum values, a set of linear model parameter values; and restoration based on the linear model of the current video block.

7. The method of 6, wherein generating the plurality of groups is based on the availability of a neighboring block of the current video block.

8. Method according to 6, in which a plurality of groups constitute S0 and S1, in which the maximum brightness value is calculated as maxL = f1(maxL _S0 , maxL _S1 ,..., maxL _Sm , where f1 is the first function and maxL _Si is the maximum brightness value group Si of a set of groups, in which the maximum chromaticity value is calculated as maxC = f2(maxC _S0 , maxC _S1 ,…, maxC _Sm , where f2 represents the second function, maxC _Si is the maximum chromaticity value of group Si, in which the minimum luminance value is calculated as minL = f3(minL _S0 , minL _S1 ,…, minL _Sm ), in which f3 represents the third function, and minL _Si is the minimum luminance value of the Si group, where the minimum chrominance value is calculated as minC = f4(minC _S0 , minC _S1 , ..., minC _Sm ), in which f4 represents the fourth function, and minC _Si is the maximum chromaticity value from the group Si, and, in which the parameters of the linear model Contains α and β, which are calculated as α = ( maxC − minC )/( maxL − minL ) and β = minC − α×minL.

9. The method of 8, wherein the upper left sample of the chrominance block is (x, y), wherein the width and height of the chrominance block are W and H, respectively, and wherein the group of adjacent chrominance samples contains.

Sample A with coordinates (x - 1, y),

Sample D with coordinates (x - 1, y + h - 1),

Sample J with coordinates (x, y - 1) and

Sample M with coordinates (x + w - 1, y - 1).

10. The method of 9, in which the upper left adjacent block and the upper block of the current video block are available, in which the maximum luminance and chrominance values and the minimum luminance and chrominance values for group S0 (maxL _S0 , maxC _S0 , minL _S0 and minL _S0 , respectively) are based on on samples A and D, in which the maximum luminance and chrominance values and minimum luminance and chrominance values for group S1 (maxL _S1 , maxC _S1 , minL _S1 and minL _S1, respectively) are based on samples J and M, in which

maxL = ( maxL _S0 + maxL _S1 )/2, maxC = ( maxC _S0 + maxC _S1 )/2,

minL = ( minL _S0 + minL _S1 )/2 and minC = ( minC _S0 + minC _S1 )/2.

11. The method of 9, wherein the top left adjacent block of the current video block is available, and wherein maxL, maxC, minL and minC are based on samples A and D.

12. The method of 9, wherein a higher adjacent block of the current video block is available, and wherein maxL, maxC, minL and minC are based on the J and M samples.

13. Method according to 6, in which the parameters of the linear model contain α and β, which are calculated as

α = 0 and β = 1 << ( bitDepth − 1 ),

in which BitDepth is the bit depth of the chroma sample.

14. The method of 6, wherein generating the plurality of groups is based on the height or width of the current video block.

15. A method for processing video, containing:

Generating downsampled luminance and chrominance samples by downsampling luminance and chrominance samples of an adjacent block of the current video block with height (H) and width (W);

Determination, based on downsampled luma and chrominance samples, of a set of values for the linear model parameters for the current video block; And

Linear model-based reconstruction of the current video block.

16. The method of 15, wherein the downsampling is based on height or width.

17. Method according to 16, in which W <H.

18. Method according to 16, where W> H.

19. The method of 15, wherein the top left sample of the current video block is R[0, 0], wherein the downsampled chroma samples comprise R[-1, k × H/W] samples, and where K is a non-negative integer of 0 to W-1.

20. The method of 15, wherein the top left sample of the current video block is R[0, 0], wherein the downsampled chroma samples comprise R[K × H/W, -1] samples, and K is a non-negative integer of 0 to H-1.

21. The method of 15, wherein the refinement process is performed on the downsampled luma and chrominance samples before using the determination of a set of values for the linear model parameters for the current video block.

22. The method of 21, wherein the refinement process comprises a filtering process.

23. The method of 21, wherein the refinement process comprises a nonlinear process.

24. The method according to 15, in which the parameters of the linear model are α and β, in which α = (C1−C0)/(L1−L0) and β = C0 − αL0, where C0 and C1 are chroma samples, and in which L0 and L1 are luminance samples.

25. The method of 24, wherein C0 and L0 are based on S downsampled luma and chrominance samples, denoted {Lx1, Lx2, ..., LxS} and {Cx1, Cx2, ..., CxS}, respectively, where C1 and L1 are based on T downsampled luma and chrominance samples, denoted {Ly1, Ly2, …, LyT} and {Cy1, Cy2, …, CyT}, respectively,

in which, C0 = f0(Cx1, Cx2, …, CxS), L0 = f1(Lx1, Lx2, …, LxS), C1 = f2(Cy1, Cy2, …, CyT) and L1 = f1(Ly1, Ly2, ..., LyT), and

In which f0, f1, f2 and f3 are functions.

26. Method according to 25, in which f0 and f1 are the first function.

27. Method according to 25, in which f2 and f3 are the second function.

28. The method according to 25, in which f0, f1, f2 and f3 represent the third function.

29. Method according to 28, in which the third function is an averaging function.

30. Method according to 25, in which S = T.

31. Method according to 25, in which {lx1, lx2, ..., lxs} are the minimum samples of the group of luminance samples.

32. Method according to 25, in which {lx1, lx2, ..., lxs} are the largest samples of the group of luminance samples.

33. The method of 31 or 32, wherein the group of luminance samples contains all adjacent samples used in VTM-3.0 to obtain the parameters of the linear model.

34. The method of 31 or 32, wherein the group of luminance samples contains a subset of neighboring samples used in VTM-3.0 to obtain parameters of the linear model, and wherein the subset excludes all neighboring samples.

35. The method of 1, wherein two or more chroma samples are selected from one or more left columns, top row, top right row, or bottom left column relative to the current video block.

36. The method of 1, wherein samples are selected based on the height ratio of the current video block to obtain the width of the current video block.

37. The method of 1, wherein two or more chroma block samples are selected based on the encoding mode of the current video block.

38. The method of 37, wherein the encoding mode of the current video block is a first linear mode that is different from a second linear mode that uses only left adjacent samples, and a third linear mode that uses only top adjacent samples in which the coordinates of the top left sample of the current video block are (x, y) and, where the width and height of the current video block are W and H, respectively.

39. The method of 38, wherein the two or more chroma samples comprise samples with coordinates (x-1, y), (x, y-1), (x-1, y + h-1) and (X + W- 1, Y-1).

40. The method of 38, wherein the two or more chroma samples comprise samples with coordinates (X-1, Y), (x, y-1), (x - 1, y + h - h/w -1) and ( X + W-1, Y-1) and where H> W.

41. The method of 38, wherein the two or more chroma samples comprise samples with coordinates (X-1, Y), (x, y-1), (x - 1, y + h -1) and (x + w - w/h-1, y-1) and where h <w.

42. The method of 38, in which two or more chroma samples contain samples with coordinates (x-1, y), (x, y-1), (x-1, y + h - max (1, H/w) ) and (x + w- max (1, w/h), y-1).

43. The method of 38, in which two or more chroma samples contain samples with coordinates (x, y-1), (x + w/4, y-1), (x + 2 * w/4, y-1) and (x + 3 * w/4, y - 1).

44. The method of 38, in which two or more chroma samples contain samples with coordinates (x, y-1), (x + w/4, y-1), (x + 3 * w/4, y - 1) and (x + w - 1, y -1).

45. The method of 38, wherein the two or more chrominance samples comprise samples with coordinates (x, y-1), (x + (2w)/4, y-1), (x + 2 * 2W)/4, Y -1) and (x + 3 * (2w)/4, y - 1).

46. The method of 38, wherein the two or more chrominance samples comprise samples with coordinates (x, y-1), (x + (2w)/4, y-1), (x + 3 * 2 W)/4, y - 1) and (x + (2w) -1, y-1).

47. The method of 38, wherein the two or more chroma samples contain samples with coordinates (x-1, y), (x -1, y + h/4), (x -1, y + 2 * H/4) and (x -1, y + 3 * h/4).

48. The method of 38, wherein the two or more chrominance samples contain samples with coordinates (x - 1, y), (x - 1, y + 2 * h/4), (x -1, y + 3 * H/ 4) and (x -1, y + h-1).

49. The method of 38, wherein the two or more chrominance samples comprise samples with coordinates (X-1, Y), (x -1, y + (2H)/4), (x -1, y + 2 * (2H )/4) and (x -1, y + 3 * (2H)/4).

50. The method of 38, wherein the two or more chrominance samples comprise samples with coordinates (X-1, Y), (x - 1, y + 2 * (2H)/4), (x -1, Y + 3 * (2H)/4) and (x -1, y + (2H) -1).

51. The method as in any one of 39-50, wherein exactly two of the four samples are selected to determine a set of values for the parameters of the linear model.

52. Method according to any 1-51.

53. A video encoding device comprising a processor configured to perform the method of any 1-51.

54. An apparatus in a video system comprising a processor and a read-only memory with instructions thereon, wherein the instructions, when executed by the processor, cause the processor to execute the method of any one of 1-51.

55. A computer program product stored on a non-transitory computer readable medium, the computer program product includes program code for performing the method of any one of 1-51.

As is apparent from the foregoing, specific embodiments of the present invention have been described herein for purposes of illustration, but various modifications may be made within the scope of the present invention. Accordingly, the present invention is not limited except by the appended claims.

Implementations of the subject matter and functional operations described in this patent document may be embodied in various systems, digital electronic circuitry, or computer software, firmware, or hardware incorporating the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Implementations of the subject matter described in this specification may be implemented in the form of one or more computer program products, i.e. one or more modules of computer program instructions, encoded on a tangible and non-transitory computer-readable medium, for executing or for controlling the operation of a data processing device. The computer-readable medium may be a computer-readable storage device, a computer-readable storage substrate, a memory device, a composition affecting a computer-readable transmission signal, or a combination of one or more of these. The term "data processing unit" or "data processing apparatus" covers all devices, apparatus and machines for processing data, including by way of example a programmable processor, a computer, or a plurality of processors or computers. In addition to the hardware, the device may include code that configures the execution conditions of said computer program, such as code that configures processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of these.

A computer program (also known as a program, software, software application, script, or code) can be written in any form of a programming language, including compiled or interpreted languages, and can be deployed in any form, including as a stand-alone program or a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file on a file system. A program may be stored in part of a file that contains other programs or data (for example, one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (for example, files that store one or more several modules, subroutines or pieces of code). A computer program may be deployed to run on a single computer or on multiple computers that are located at one location or distributed across multiple locations and interconnected via a communications network.

The processes and logical flows described in this specification may be executed by one or more programmable processors executing one or more computer programs to perform functions that operate on input data and generate output data. Processes and logic flows can also be executed, and the device can also be implemented as a dedicated logic circuit, such as an FPGA (Field Programmable Gate Array) or ASIC (Application Application Integrated Circuit).

Processors suitable for executing a computer program include, by way of example, both general purpose and special purpose microprocessors, and any type of digital computer. Typically, the processor receives instructions and data from read-only memory or random-access memory, or both. The basic elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Typically, the computer will also include, or operatively coupled to, for receiving data or transmitting data, or both, one or more mass storage devices, such as magnetic, magneto-optical disks, or optical disks. However, the computer should not have such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of read-only memory, memory and information devices, including, by way of example, semiconductor memory devices such as EPROMs, EEPROMs, and flash memory devices. The processor and memory can be supplemented or included in the system with special-purpose logic circuitry.

The specification together with the drawings is to be considered as an example only, in which exemplary means example. As used herein, the preposition “or” covers the meaning “and/or” unless the context clearly indicates otherwise.

This patent document contains many distinctive features, but these are not to be construed as limitations on the scope of any invention or what may be claimed, but rather as descriptions of features that may be specific to particular embodiments of particular inventions. Specific features that are described in this patent document in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of one embodiment may also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although previously described features may be considered to operate in certain combinations and even initially claimed as such, one or more features from a claimed combination may, in some cases, be excluded from the combination and the claimed combination may be used as a subcombination or subcombination changes.

Likewise, while the drawings depict operations in a particular order, that order should not be construed as being required to perform such operations, as the order indicated, or that all of the illustrated operations must be performed to obtain the desired results. Moreover, the separation of various system components in the embodiments described in this patent document should not be understood as requiring separation in all embodiments.

Only a few implementations and examples are described, and other implementations, improvements and variations may be made based on the description and drawings that are given herein.

Claims (59)

1. A method for processing video data, containing the steps of: determine, for conversion between the current video video block, which is a chroma block and the video bitstream, intercomponent linear model (CCLM) parameters based on at least selected chroma samples selected from adjacent chroma samples for the current video block, wherein the positions of the selected chroma samples are obtained from a first position shift value (F) and a value step value (S), where F and S are obtained based at least on the availability of adjacent chrominance samples of the current video block and the size of the current video block; applying CCLM to the luminance samples located in the luminance block corresponding to the current video block to obtain prediction values of the current video block; And perform a transformation based on the prediction values, wherein selected chrominance samples are a subset of neighboring chroma samples based on the size of the current video block, and CCLM is an intra-frame prediction mode, adjacent chroma samples contain left adjacent chroma samples, upper adjacent chroma samples, upper right adjacent chroma samples, or lower left adjacent chroma samples relative to the current video block, in response to neighboring chrominance samples of the current video block being unavailable, the prediction values of the current video block are set to default values, the default value is 1<<(BitDepth-1), where BitDepth is the bit depth of the chroma samples, F=Floor(M/2 ⁱ ), where M is the number of adjacent chroma samples used to obtain the selected chroma samples in the horizontal direction, or F=Floor(N/2 ⁱ ), where N is the number of adjacent chroma samples used to obtain selected chrominance samples in the vertical direction, i is 2 or 3, and the Floor operation is used to obtain the integer part of the number, S=Max(1, Floor(M/2 ^j )) or S=Max(1, Floor(N/2 ^j )), where j is 1 or 2, and the Max operation is used to obtain the maximum of a set of numbers, the CCLM mode of the current video block is one of: a first CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the upper neighboring chroma samples, a second CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the lower left neighboring samples, or a third CCLM mode in which the CCLM parameters are obtained based on the top neighboring chroma samples and the top right neighboring chroma samples, and in response to the CCLM mode being the first CCLM mode and the upper adjacent chroma samples being available, the value of M is equal to the value of W. 2. The method of claim 1, wherein both values, M and N, are less than or equal to W + H and are determined based on the CCLM mode of the current video block, where W and H are, respectively, the width and height of the current video block. 3. The method of claim 1, wherein, in response to selecting two chroma samples in the horizontal direction, the positions of the two selected chroma samples in the horizontal direction are Floor(M/4) and Floor(M/4) + Floor(M/2 ). 4. The method of claim 1, wherein in response to selecting two chroma samples in the vertical direction, the positions of the two selected chroma samples in the vertical direction are Floor(N/4) and Floor(N/4) + Floor(N/2) . 5. The method of claim 1, wherein in response to selecting four chroma samples in the horizontal direction, the positions of the four selected chroma samples in the horizontal direction are Floor(M/8), Floor(M/8) + Floor(M/4) , Floor(M/8) + 2*Floor(M/4) and Floor(M/8) + 3*Floor(M/4). 6. The method of claim 1, wherein, in response to selecting four chroma samples in the vertical direction, the positions of the four selected chroma samples in the vertical direction are Floor(N/8), Floor(N/8) + Floor(N/4 ), Floor(N/8) + 2*Floor(N/4) and Floor(N/8) + 3*Floor(N/4). 7. The method of claim 1, wherein, in response to the CCLM mode being the third mode, the top adjacent chroma samples are available and the top right adjacent chroma samples are not available, and the value of M is equal to the value of W. 8. The method of claim 1, wherein, in response to the CCLM mode being the first mode and the left adjacent chroma samples being available, the value of N is equal to the value of H. 9. The method of claim 1, wherein, in response to the CCLM mode being the second mode, left adjacent chroma samples are available and lower left chroma samples are not available, and the value of N is equal to the value of H. 10. The method of claim 1, wherein the conversion step comprises a substep of encoding the current video block into a bitstream. 11. The method of claim 1, wherein the conversion step comprises a substep of decoding the current video block from the bit stream. 12. A video data processing device containing a processor and permanent memory with commands written in it, causing, when executed by the processor, execution by the specified processor: determining, for conversion between a current video video block representing a chrominance block and a video bitstream, intercomponent linear model (CCLM) parameters based on at least selected chroma samples selected from adjacent chroma samples for the current video block, wherein the positions of the selected chroma samples are derived from a first position shift value (F) and a value step value (S), where F and S are obtained based at least on the availability of adjacent chrominance samples of the current video block and the size of the current video block; applying CCLM to the luminance samples located in the luminance block corresponding to the current video block to obtain prediction values of the current video block; And performing a transformation based on the prediction values, wherein selected chrominance samples are a subset of neighboring chroma samples based on the size of the current video block, and CCLM is an intra-frame prediction mode, adjacent chroma samples contain left adjacent chroma samples, upper adjacent chroma samples, upper right adjacent chroma samples, or lower left adjacent chroma samples relative to the current video block, in response to neighboring chrominance samples of the current video block being unavailable, the prediction values of the current video block are set to default values, the default value is 1<<(BitDepth-1), where BitDepth is the bit depth of the chroma samples, F=Floor(M/2 ⁱ ), where M is the number of adjacent chroma samples used to obtain the selected chroma samples in the horizontal direction, or F=Floor(N/2 ⁱ ), where N is the number of adjacent chroma samples used to obtain selected chrominance samples in the vertical direction, i is 2 or 3, and the Floor operation is used to obtain the integer part of the number, S=Max(1, Floor(M/2 ^j )) or S=Max(1, Floor(N/2 ^j )), where j is 1 or 2, and the Max operation is used to obtain the maximum of a set of numbers, the CCLM mode of the current video block is one of: a first CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the upper neighboring chroma samples, a second CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the lower left neighboring samples , or a third CCLM mode in which the CCLM parameters are obtained based on the top adjacent chroma samples and the top right adjacent chrominance samples, and in response to the CCLM mode being the first CCLM mode and the upper adjacent chroma samples being available, the value of M is equal to the value of W. 13. A computer-readable storage medium that stores instructions that cause the processor to execute: determining, for conversion between a current video video block representing a chrominance block and a video bitstream, intercomponent linear model (CCLM) parameters based on at least selected chroma samples selected from adjacent chroma samples for the current video block, wherein the positions of the selected chroma samples are derived from a first position shift value (F) and a value step value (S), where F and S are obtained based at least on the availability of adjacent chrominance samples of the current video block and the size of the current video block; applying CCLM to the luminance samples located in the luminance block corresponding to the current video block to obtain prediction values of the current video block; And performing a transformation based on the prediction values, wherein selected chrominance samples are a subset of neighboring chroma samples based on the size of the current video block, and CCLM is an intra-frame prediction mode, adjacent chroma samples contain left adjacent chroma samples, upper adjacent chroma samples, upper right adjacent chroma samples, or lower left adjacent chroma samples relative to the current video block, in response to neighboring chrominance samples of the current video block being unavailable, the prediction values of the current video block are set to default values, the default value is 1<<(BitDepth-1), where BitDepth is the bit depth of the chroma samples, F=Floor(M/2 ⁱ ), where M is the number of adjacent chroma samples used to obtain the selected chroma samples in the horizontal direction, or F=Floor(N/2 ⁱ ), where N is the number of adjacent chroma samples used to obtain selected chrominance samples in the vertical direction, i is 2 or 3, and the Floor operation is used to obtain the integer part of the number, S=Max(1, Floor(M/2 ^j )) or S=Max(1, Floor(N/2 ^j )), where j is 1 or 2, and the Max operation is used to obtain the maximum of a set of numbers, the CCLM mode of the current video block is one of: a first CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the upper neighboring chroma samples, a second CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the lower left neighboring samples, or a third CCLM mode in which the CCLM parameters are obtained based on the top neighboring chroma samples and the top right neighboring chroma samples, and in response to the CCLM mode being the first CCLM mode and the upper adjacent chroma samples being available, the value of M is equal to the value of W. 14. A method for storing a video bitstream, comprising the steps of: determine, for conversion between the current video video block, which is a chroma block and the video bitstream, intercomponent linear model (CCLM) parameters based on at least selected chroma samples selected from adjacent chroma samples for the current video block, wherein the positions of the selected chroma samples are obtained from a first position shift value (F) and a value step value (S), where F and S are obtained based at least on the availability of adjacent chrominance samples of the current video block and the size of the current video block; applying CCLM to the luminance samples located in the luminance block corresponding to the current video block to obtain prediction values of the current video block; generating a bitstream from the current video block, based on the definition, and storing the bit stream on a non-volatile computer-readable storage medium; and selected chrominance samples are a subset of neighboring chroma samples based on the size of the current video block, and CCLM is an intra-frame prediction mode, adjacent chroma samples contain left adjacent chroma samples, upper adjacent chroma samples, upper right adjacent chroma samples, or lower left adjacent chroma samples relative to the current video block, in response to neighboring chrominance samples of the current video block being unavailable, the prediction values of the current video block are set to default values, the default value is 1<<(BitDepth-1), where BitDepth is the bit depth of the chroma samples, F=Floor(M/2 ⁱ ), where M is the number of adjacent chroma samples used to obtain the selected chroma samples in the horizontal direction, or F=Floor(N/2 ⁱ ), where N is the number of adjacent chroma samples used to obtain selected chrominance samples in the vertical direction, i is 2 or 3, and the Floor operation is used to obtain the integer part of the number, S=Max(1, Floor(M/2 ^j )) or S=Max(1, Floor(N/2 ^j )), where j is 1 or 2, and the Max operation is used to obtain the maximum of a set of numbers, the CCLM mode of the current video block is one of: a first CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the upper neighboring chroma samples, a second CCLM mode in which the CCLM parameters are obtained based on the left neighboring chroma samples and the lower left neighboring samples, or a third CCLM mode in which the CCLM parameters are obtained based on the top neighboring chroma samples and the top right neighboring chroma samples, and in response to the CCLM mode being the first CCLM mode and the upper adjacent chroma samples being available, the value of M is equal to the value of W.