RU2777779C1 - Obtaining a parameter for in-frame prediction - Google Patents

Abstract

FIELD: video technology.

SUBSTANCE: invention relates to the field of video processing, in particular to video encoding. A video processing method is proposed, which includes determining, for conversion between the current video block of video, which is a chroma block, and the encoded representation of the video, the parameters of the inter-component linear model (CCLM) based on two or four chroma samples and/or corresponding brightness samples; and performing the transformation based on the definition.

EFFECT: providing a balanced compromise between complexity and increased compression efficiency.

22 cl, 31 dwg

Description

The field of technology to which the invention belongs

The present invention relates to technologies, devices and systems for video processing.

State of the art

Despite advances in video compression, digital video still occupies 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 bandwidth demand for digital video use is expected to continue to increase.

Disclosure of the essence of the invention

The present disclosure provides descriptions of devices, systems, and methods related to digital video processing, and, for example, deriving a simplified linear model for inter-component linear model prediction mode (CCLM) in video coding. The described techniques can be applied to both existing video coding standards (eg, High Efficiency Video Coding (HEVC)), and future video coding standards (eg, Universal 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 determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, inter-component linear model (CCLM) prediction mode parameters based on chrominance samples that are selected based on W available upper neighbor samples, W being an integer ; and performing the conversion based on the determination.

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

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

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: selecting, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, chroma samples based on a position rule, the chrominance samples are used to obtain inter-component linear model (CCLM) parameters; and performing a transformation based on the determination, wherein the position rule specifies to select chrominance 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 converting between the current video block, which is a chrominance block, and the encoded representation of the video, the positions at which the luminance samples are downsampled, in which the downsampled luminance samples are used to determine the parameters of the inter-component linear model (CCLM) based on chrominance samples and downsampled luminance samples, in which the downsampled luminance samples are at positions corresponding to positions of the chrominance samples that are used to derive the CCLM parameters; and performing the transformation based on the determination.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: determining, for converting between the current video block, which is a chrominance block, and the encoded video representation, a method for obtaining inter-component linear model (CCLM) parameters using chrominance samples and luma samples based on a coding condition associated with the current video block ; and performing the conversion based on the determination.

In another exemplary aspect, the technology of the present disclosure may be used to provide a video processing method. The method comprises: determining, for converting between the current video block, which is a chrominance block, and the encoded video representation, whether the maximum values and/or minimum values of the luma component and the chrominance component should be obtained, which are used to obtain the parameters of the inter-component linear model (CCLM) based on the availability of the left neighbor block and the top neighbor block of the current video block; and performing the transformation based on the determination.

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

In yet another exemplary aspect, an apparatus is provided that is capable of performing the method described above. The device may include a processor that is programmed to implement this method.

In yet another exemplary aspect, a video decoder apparatus 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 the drawings

1 shows an example of sample positions used to derive the weights of a linear model used for intercomponent prediction.

2 shows an example of classifying neighboring samples into two groups.

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

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

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

5 shows an example of a straight line between the minimum and maximum luminance values as a function of the respective chrominance samples.

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

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 the top left neighbor block.

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

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

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.

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

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

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

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

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

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

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

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

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

Figa and 22B show examples of the process of obtaining the LM parameter with four entries. FIG. 22A shows an example where both top and left neighbor samples are available, and FIG. 31B shows an example where only top neighbor samples are available and top right is unavailable.

23 shows examples of adjacent samples to obtain LIC parameters.

Implementation of the invention

Due to the increasing demand for higher resolution video, video coding methods and techniques have been applied in modern technology. Video codecs typically include electronic circuitry or software that compresses or decompresses digital video and is constantly being improved to provide higher coding efficiency. The video codec converts uncompressed video to a compressed format, or vice versa. There are complex relationships between video quality, amount of data used to represent video (determined by bit rate), complexity of encoding and decoding algorithms, sensitivity to data loss and error, ease of editing, random access, and end-to-end latency. The compressed format generally conforms to standard video compression specifications, such as the High Efficiency Video Coding (HEVC) standard (also known as H.265 or MPEG-H Part 2), the Universal Video Coding (VVC) standard to be completed, or other current and /or future video coding standards.

Embodiments of the disclosed technology may be applied to existing video coding standards (eg, HEVC, H.265) and future standards to improve processing performance. Section headings are used throughout this document to improve the readability of the description, and in no way is the description or embodiments (and/or implementations) limited to the respective sections.

1. Embodiments of intercomponent prediction

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

1.1 Intercomponent Linear Model (CCLM) Examples

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

представляет собой предсказанные выборки цветности в CU и

представляет собой восстановленные выборки яркости после понижающей дискретизации одинакового CU для цветовых форматов 4:2:0 или 4:2:2, где

представляет собой восстановленные выборки яркости одного и того же CU для цветового формата 4:4:4. CCLM параметры α и β получены путем минимизации ошибок регрессии между соседними восстановленными выборками яркости и цветности вокруг текущего блока следующим образом:

is the predicted chrominance samples in the CU and

represents the downsampled reconstructed luma samples of the same CU for 4:2:0 or 4:2:2 color formats, where

represents the reconstructed luminance samples of the same CU for the 4:4:4 color format. The CCLM parameters α and β are obtained by minimizing the regression errors between adjacent reconstructed luma and chrominance samples around the current block as follows:

представляет собой исходные (для цветного формата 4:4:4) или с понижающей дискретизацией (для цветных форматов 4:2:0 или 4:2:2) верхние и левые соседние восстановленные выборки яркости или исходные и левые соседние восстановленные выборки яркости,

представляет верхние и левые соседние восстановленные выборки цветности и значение

равно удвоенной минимальной ширине и высоты текущего блока кодирования цветности.

represents the original (for 4:4:4 color format) or downsampled (for 4:2:0 or 4:2:2 color formats) top and left adjacent reconstructed luma samples, or the original and left adjacent reconstructed luma samples,

represents the top and left adjacent reconstructed chrominance samples and value

is equal to twice the minimum width and height of the current chrominance coding block.

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

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

In some embodiments, the CCLM prediction mode also includes prediction between two chrominance components, for example, the Cr (red-difference) component is predicted from the Cb (cyan-difference) component. Instead of using the reconstructed sample signal in the residual region, CCLM Cb-to-Cr prediction is applied. This is done by adding the weighted reconstructed Cb residual to the original Cr intra prediction to form the final Cr prediction:

представляет собой восстановленную Cb выборку остатка на позиции (i, j).

represents the reconstructed Cb sample of the remainder at position (i, j).

In some embodiments, the scaling factor α may be obtained in a similar manner as in CCLM luminance-to-chrominance prediction. The only difference is the addition of the regression cost about 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:

представляет собой соседние восстановленные Сb выборки,

представляет собой соседние восстановленные Cr выборки и λ равна

.

is the adjacent reconstructed Cb samples,

is the adjacent reconstructed Cr samples and λ is equal to

.

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

1.2 Multiple CCLM Model Examples

JEM uses two CCLM modes: single CCLM model mode and multiple CCLM model (MMLM) mode. As indicated by the name, for chrominance sample prediction, the CCLM single model mode uses one linear model from the luma samples for the entire CU, and MMLM can use two models.

In MMLM, neighboring luminance 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 (ie, specific α and β are obtained for a specific group). Moreover, the samples of the current luma block are also classified based on the same rule for classifying neighboring luma samples.

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

1.3 Examples of downsampling filters in CCLM

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

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

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

In some embodiments and for MMLM mode, the encoder may alternatively select one of the four additional luminance downsampling filters to be applied for prediction at 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:

1.4 Multidirectional LM (MDLM)

This current implementation offers multi-directional LM (MDLM). MDLM uses two additional CCLM modes: LM-A, in which the linear model parameters are only obtained based on the top adjacent (or higher adjacent) samples, as shown in FIG. 4A, and LM-L, in which the linear model parameters are obtained only on the basis of 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 the parameters α and β of the linear model by a straight line equation, the so-called two-point method. The 2 points (luma and chrominance pair) (A, B) are the minimum and maximum values within a set of adjacent luma 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 split operation required to obtain α should be omitted and should be replaced with 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 to iShift, α is set to a, and β is set to b. In addition, g_aiLMDivTableLow and g_aiLMDivTablehigh are two tables each with 512 entries, in which each entry stores a 16-bit integer.

To get the chrominance predictor, as for the current VTM implementation, 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 examples in VVC

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 have been adopted in VTM-3.0.

1.7 Examples of local illumination compensation in JEM

Local Illumination Compensation (LIC) is based on a linear model for illumination changes using a scaling factor a and an offset b. And is used or disabled adaptively for each encoded coding unit (CU) in the intercoding mode.

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

When a CU is encoded using 2NX2N merge mode, the LIC flag is copied from adjacent blocks in the same way as motion information is copied in merge mode; otherwise, the LIC flag is signaled to the CU to indicate whether LIC is applied or not.

When using LIC for an image, an additional check of the RD level CU is required to determine if LIC is applied or not for the CU. When LIC is applied to CU, absolute difference mean sum removed (MR-SAD) and absolute Hadamard mean difference removed sum (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 change in illumination between the current image and its reference images. To identify this situation, the encoder calculates the histograms of the current picture and each reference picture of the current picture. If the histogram difference between the current image and each reference image of the current image is less than a predetermined 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 mode to replace the LMS approach of the LM mode. Although the new method reduces the number of additions and multiplications in CCLM, the following technical problems need to be solved:

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

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

3 Exemplary methods for inter-component prediction in video coding

Embodiments of the present invention solve the technical problems of existing implementations, thereby providing video coding with higher coding efficiency and lower computational complexity. Simplified linear models for inter-component prediction based on the disclosed technology can enhance both existing and future video coding standards, which are explained in the following examples, described for various implementations. The examples of disclosed technology presented below explain the general concepts and are not intended to be interpreted as limiting. In the example, unless explicitly stated otherwise, the 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 upper neighbor samples to obtain a linear model, or other kinds of methods that use reconstructed luma samples to obtain chrominance prediction blocks. All LM modes that are neither LM-L nor LM-A are called normal LM modes.

и Signshift (x, s) определяется какIn 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 current chrominance block are denoted by H and W, respectively.

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

A: top select left: [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 sample left: [x-1, y + H-1],

E: extended lower left upper selection: [x-1, y + H],

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

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

I: Extended lower selection on the left: [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 mean 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 mean sample above: [x + W + W / 2-1, y-1],

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

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

Example 1 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 luminance samples of the selected chrominance samples. Alternatively, the acquisition also depends on the respective luminance samples of the selected chrominance samples, such as 4:4:4 color format.

b. For example, the parameters α and β in CCLM are derived from chrominance samples at 2 ^S (for example, 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};

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

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

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

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

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

xviii. 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};

xxi. 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 derived from 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 F and O;

(g) position G and P;

(h) position I and Q;

ii. Any two distinct 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) positions I and E;

(p) position I and F;

(q) position I and G;

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

(a) position J and K;

(b) position J and L;

(c) position J and M;

(d) position J and N;

(e) position J and O;

(f) position J and P;

(g) position J and Q;

(h) position M and K;

(i) position M and L;

(j) position N and K;

(k) position N and L;

(l) Q and K position;

(m) Q and L positions;

(n) position Q and M;

(o) position Q and N;

(p) Q and O position;

(q) position Q and P;

(r) the 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 brightness values to obtain the parameters α and β in CCLM using the 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 may be 2, 4, 6 or 8;

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

ii. Only chrominance 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 upper 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, positions are displayed that can be signaled from an encoder to a 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 the least squares method, as shown in equation (2) and equation (3). In equation (2) and equation (3), N is the number of selected samples.

i. A pair of selected chrominance samples are used to obtain the parameters α and β in a point-to-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 neighboring block is available.

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

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 ) are of different accuracy, for example, to obtain a chrominance prediction CP from its corresponding downsampled luminance sample LR is calculated as

с (α₁, β₁), но

with (α ₁ , β ₁ ), but

с (α₂, β₂) Sh₁ не равен Sh₂, то параметры должны быть смещены до объединения. Предположим, что Sh₁ > Sh₂, затем до объединения параметры должны быть смещены как:

with (α ₂ , β ₂ ) Sh ₁ is not equal to Sh ₂ , then the parameters must be shifted before combining. Assume that Sh ₁ > Sh ₂ , then prior to combining the parameters should be shifted as:

. Затем окончательная точность равна (α₂, β₂).

. Then the final precision is (α ₂ , β ₂ ).

Затем окончательная точность равна (α₂, β₂).

Then the final precision is (α ₂ , β ₂ ).

. Затем окончательная точность равна (α₂, β₂).

. Then the final precision is (α ₂ , β ₂ ).

. Затем окончательная точность равна (α₁, β₁)(With)

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

b. Some examples of positions in groups 1 and groups 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: Position J and M, group 2: Position N and Q, 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: Position J and K, group 2: Position L and M, 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 respective luminance sample values, denoted as L0 and L1 (L0<L1), are input values. By performing the two-point method, one can obtain α and β with input values as

Bit depths of luma samples and chrominance samples are denoted 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 specific intra prediction mode (eg, DM mode, DC, or planar), it is used using the CCLM mode to obtain a 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.

илиi.

or

илиii.

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 might be

используется в противном случае пример ii.(b) For example, example i is used if

used otherwise example ii.

используется в противном случае пример ii.(c) For example, example i is used if

used otherwise example ii.

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

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

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

In one example, M[k-Z] = ((1 << S) + Off)/k, where S is an integer specifying precision, e.g. S = F. Off is an offset, e.g. Off = (k + Z) >> 1. Z defines 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 to query the lookup table (k-Z < 0 or k-Z > = V), α is output as 0.

v. For example,

или

or

vi. To obtain the chrominance prediction CP from the corresponding (eg downsampled for 4:2:0) luma sample LR is computed as

или

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 V, is 2 ^P , where P is an integer such as 5, 6, 7, or 8. Alternatively, V is set to 2 ^P - M (eg, M is 0).

ix. Suppose α = P/Q (e.g. Q = L1-L0, P = C1-C0 or they get it in other ways), then α is calculated with the lookup table as α = Shift(P×M[k−Z], D ) or α = SignShift(P×M[k−Z], D), where k is the key (index) to query for 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 a 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 when Q <= kMax and k = Shift(Q, W) when Q > kMax. For example, W is chosen as the smallest positive integer, which ensures that 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 the transient variable can exceed the range represented by the restricted bit, then a constraint or right shift must be performed to be within the restricted bits.

Example 4 One chrominance block can use multiple linear models and the choice of multiple linear models depends on the position of the chrominance samples within the chrominance block.

a. In one example, LM-L and LM-A mode can be combined in one chrominance 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) predict LM-A and other samples are predicted by LM-L.

With. Suppose that the LM-L and LM-A predictions for the sample at position (x, y) are denoted as 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 (e.g. w1 = 2, w2 = 2) if x == y,

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

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

Example 5 It is proposed that adjacent samples (including chrominance samples and their corresponding luma samples that can be downsampled) are divided into N groups. The maximum luminance value and the minimum luminance value for the k-th group (with k = 0, 1, ..., N-1) are denoted as MaxL _k and MinL _k and their respective 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 two-point method, one obtains α and β 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, eg 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, the samples (or downsamples) located on the top rows can be classified into one group and the samples (or downsamples) located in the left column of the 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, the samples can be classified into two groups.

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

(2) For a sample with coordinate (x, y) located in the left column, is classified into group S0 if y% P = Q, in which P and Q are integers, for example, P = 2, Q = 1, P = 2, Q = 0 or P = 4, Q = 0; Otherwise, it is classified in 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 partials from adjacent samples (or downsampled samples) are used for the grouped N.

e. Number of groups (e.g. N) and/or indexes of selected groups and/or functions (f1/f2/f3/f4) can be pre-defined 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 defined from positions A and D; MaxL ₁ /MaxC ₁ and MinL ₁ /MinC ₁ are defined from position 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 default values if the top neighbor block is not available. For example, α = 0 and β = 1 << (bitDepth -1), in which bitDepth is the bit depth of the chrominance samples.

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

(1) Alternatively, α and β are set to default values if the left neighbor block is not available. For example, α = 0 and β = 1 << (bitDepth -1), in which bitDepth is the bit depth of the chrominance samples.

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

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

i, in one example, the two samples with the highest 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 proposed 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. for example, K = 2.

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

(c) If one of LM-L and LM-A cannot be applied, no flag should be signaled to indicate the use of LM-L or LM-A.

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

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

(b) In one example, if the upper left neighbor block is not available, then it is considered as not applying the CCLM mode.

(c) In one example, if the upper left neighbor block is not available, then it is considered as applying the CCLM mode.

(d) In one example, if the top-left neighbor block is not intra-coded, then it is considered as not applying the CCLM mode.

(e) In one example, if the top-left neighbor block is not intra-coded, then it is considered as applying the CCLM mode.

Example 8 DM and LM mode indications or codewords can be encoded in different orders from sequence to sequence/image to image/tile to tile/block to block.

(a) The order in which the DM and LM indications are encoded (e.g., first, the LM mode code, if not, then the DM mode code; or, first, the code, whether it is 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 with the LM mode, then the LM mode indication is encoded first.

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

(d) Alternatively, when the top 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, ordering indications may be signaled in SPS/VPS/PPS/image header/segment header/tile group header/LCUs/LCU/CUs.

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

(a) By means of LM mode or LM-L mode, the adjacent sample RecC[x-1, y+d] can be used in which d is in the range [T, S]. 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 yet another example, T=0 and S=4H.

(b) By LM mode or LM-A mode, an adjacent sample of 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 yet another example, T=0 and S=4W.

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

(a) In one example, whether and how the downsampling process should be performed may depend on W and H.

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

(c) In one example, adjacent chrominance samples and their corresponding luminance samples (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 chrominance 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 chosen to be used to obtain α and β.

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

(ii) In one example, one chrominance sample in each of the W/H chrominance samples is selected to obtain α and β. Other chrominance 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 taken 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 Adjacent original-recovered/downsampled samples and/or original-recovered/downsampled samples may be further refined before being used in a linear model prediction process or an intercomponent color prediction process.

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

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

(c) It is proposed that several adjacent samples (including the chrominance samples and their corresponding luminance samples that can be downsampled) be selected to compute 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 as Lx1, Lx2, ..., LxS, and their respective chrominance samples, denoted as Cx1, Cx2, ... CxS, are used to obtain C0 and L0 and T adjacent luma samples (may be downsampled) denoted Ly1, Ly2, ..., LyT and their respective chrominance samples denoted Cy1, Cy2, ... CyT are used to derive 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 an averaging function.

(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 adjacent samples used in VTM-3.0 to obtain linear CCLM parameters.

2. For example, the group of luminance samples includes partial adjacent 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 the group of luminance samples.

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

2. For example, the group of luminance samples includes partial adjacent 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 downsampling neighbor or neighbor samples based on the largest downsampling neighbor or neighbor sample in a given set of downsampling neighbor or neighbor samples.

(a) In one example, the largest adjacent or downsampled adjacent sample located at position (x0, y0) is denoted. Then, samples in the region (x0-d1, y0), (x0, y0-d2), (x0 + d3, y0), (x0, y0 + d4) can be used to select other samples. The number of integers {d1, d2, d3, d4} may 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, the smallest adjacent or downsampled adjacent sample located at position (x1, y1) is denoted. Then, samples in the region (x1-d1, y1), (x1, y1-d2), (x1 + d3, y1), (x1, y1 + d4) can be used to select other samples. The integers {d1, d2, d3, d4} may 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 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 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 14 The choice 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 left column or top row or top right row or bottom left column. 10 depicts the concepts of left column/top row/top right row/bottom left column relative to a block.

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

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

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

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

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

(i) If both the left column and the top row are available, then two samples of the left column and two top rows may be selected. They can be located at (assume 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 top row samples 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 width/height. For example, four samples are selected when W > 2 and two samples are selected when W = 2.

4. The selected selections 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 - one).

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

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

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

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

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

4. Selected samples 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) /four).

For example if the left column is available or when the 1st bottom left selection will be available.

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

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

(iv) For the examples above, 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 according to example 11(d)(ii).

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

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

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

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

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

a. In one example, W may be set to the width of the current block.

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

With. In one example, when both top and left boxes are available, W may be set to the width of the current box.

i. Alternatively, when the left box is not available, W can be set to (L * current box width), in which L is an integer value.

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

d. In one example, W may be coded mode dependent.

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

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

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

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

i. For example, P = 2 ⁱ , where 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 , where 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 , where 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 , where n is an integer such as 1 or 2.

j. kMax and/or F and/or S and/or offset may depend on the prediction mode (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, adjustments are made if the current block is LM encoded, both left and top adjacent samples are available, and W> = 4.

about. For example, kMax = 3, F = W/8, S = W/4, offset = 0. Alternatively, further adjustments are made if the current block is to encode LM, only upper adjacent samples are available, and W >= 4.

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

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

Example 17 It is proposed to select left adjacent chrominance samples (and/or their respective luma samples that can be downsampled) based on a first position offset value (denoted as F) and a stride value (denoted as S). Assume that the height of the available left adjacent samples to be used is H.

a. In one example, H may be set to the height of the current block.

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

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

i. Alternatively, when the top box is NOT available, H can be set to (L * height of the current box), where 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 bottom left sample.

iii. Alternatively, H can be set to (current box height + current box width) if accessibility of top right neighbor boxes is needed.

(a) In one example, the same H top neighbor samples are selected for LM-A mode and LM mode when left neighbor samples are unavailable.

d. In one example, H may be coded mode dependent.

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), where L is an integer value, if the current block is encoded as LM-L mode.

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

(b). Alternatively, W can be set to (current box height + current box width) if the required bottom left adjacent boxes are available.

(c) In one example, the same W left adjacent samples are selected for LM-L mode and LM mode when no higher adjacent samples are available.

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

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

i. For example, P = 2 ⁱ , where 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 , where 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 , where 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 , where n is an integer such as 1 or 2.

j. kMax and/or F and/or S and/or offset may depend on the prediction mode (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, further adjustments are made if the current block is LM encoded, both left and top adjacent samples are available, and H>=4 .

about. For example, kMax=3, F= H/8, S= H/4, offset=0. Alternatively, further adjustments are made if the current block is LM coded, only upper adjacent samples are available, and H>=4.

R. For example, kMax=3, F= H/8, S= H/4, offset=0. Alternatively, in addition, settings are made if the current block is encoded with 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 luma samples, which may be downsampled) are selected to obtain linear model parameters.

a. In one example, maxY/maxC and minY/minC are obtained from two or four adjacent chrominance samples (and/or their respective luma samples, which may be downsampled) and then used to derive linear model parameters using a 2-point approach.

b. In one example, given two adjacent chrominance samples (and/or their respective luminance samples that may be downsampled) that are selected to obtain maxY/maxC and minY/minC, minY is set to the smallest luma sample value and minC is the corresponding chrominance 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 chrominance samples (and/or their respective luminance samples, which may be downsampled) that are selected to produce maxY/maxC and minY/minC, the luminance samples and their respective chrominance samples are divided into two arrays G0 and G1, each containing two luminance samples and their respective luminance samples.

i. Assume that the four luma samples and their respective chrominance samples are designated as S0, S1, S2, S3, and they can be divided into two groups in any order. For example:

(a) G0={S0, S1}, G1={S2, S3};

(b) G0={S1, S0}, G1={S3, S2};

(c) G0={S0, S2}, G1={S1, S3};

(d) G0={S2, S0}, G1={S3, S1};

(e) G0={S1, S2}, G1={S0, S3};

(f) G0={S2, S1}, G1={S3, S0};

(g) G0={S0, S3}, G1={S1, S2};

(h) G0={S3, S0}, G1={S2, S1};

(i) G0={S1, S3}, G1={S0, S2};

(j) G0={S3, S1}, G1={S2, S0};

(k) G0={S3, S2}, G1={S0, S1};

(l) G0={S2, S3}, G1={S1, S0};

(m) G0 and G1 may be variable.

ii. In one example, the luma sample value G0[0] and G0[1] are compared, if the luminance sample value G0[0] is greater than the luminance sample value G0[1], then the luminance samples and its corresponding chrominance sample G0[0] will change from G0 [1].

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

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

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

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

(a) Alternatively, if the luma sample value G0[0] is greater than or equal to the luma 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 luma sample value G1[1], then the luminance sample and its corresponding chroma 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 luminance sample and its corresponding chrominance sample G1[0] will be swapped with G1[1].

iv. 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 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 swap.

(b) One example compares the luminance sample value G0[1] and G1[0] if the luminance sample value G0[1] 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 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 swap.

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] will swap.

(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 swap.

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

(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 swap.

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

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

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

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

d. In one example, if there are only two adjacent chrominance samples (and/or their respective luma samples that can be downsampled), they are first padded to obtain four chrominance samples (and/or their respective luma samples), then four chroma samples. (and/or their respective luma samples) are used to obtain the CCLM parameters.

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

Example 19: In all of the above examples, the selected chrominance samples should 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 which 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 restriction may be applied when the current block is encoded using the LM-A mode.

ii. Alternatively, in addition, the above restriction may be applied when the current block is encoded with LM-A mode or normal LM mode with the top row available but the left column not available.

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

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

ii. Alternatively, in addition, the above restriction may be applied when the current block is encoded using LM-L mode or normal LM mode with the top row not available but the left column available.

Example 20

In one example, only adjacent luminance samples need to be downsampled at positions where corresponding chrominance samples are required to obtain CCLM parameters.

Example 21

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

a. Alternatively, how to perform the methods disclosed in this document may depend on the bit depth (eg, 8-bit or 10-bit).

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

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

d. Alternatively, how to conduct the methods disclosed in this document 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 obtain the CCLM parameters may depend on the availability of neighboring samples. For example, the maximum/minimum values for the luminance and chrominance components used to derive the CCLM parameters cannot be obtained if both left and top neighbor blocks are not available.

a. Whether to obtain the maximum/minimum values of the luminance and chrominance components used to obtain the CCLM parameters may depend on the number of adjacent samples available. For example, the maximum/minimum values for the luminance and chrominance components used to derive 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 retrieved if if numSampL + numSampT == 0. In the two examples, numSampL and numSampT are the number of available adjacent samples to the left and above adjacent 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 derive 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 select samples left and above 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 use a linear model.

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

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

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

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

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

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

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

iv. Whether the methods described above should be used and/or how specific positions should be determined may depend on the block size.

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

i. For example, N is 4.

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

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

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

(a) in one example, L is set to 4

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

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

vi. In one example, the selection of N sample coordinates 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 adjacent samples (which may be downsampled) of the current block and corresponding adjacent samples (which may respectively be downsampled) of the reference block used to derive parameters may be selected for use in the LIC, based on sample positions.

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

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

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

vi. For example, the top samples may be selected with a first position offset value (denoted as F) and a stride value (denoted as S), which may depend on the measurement of the current block and the availability of adjacent blocks.

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

vii. For example, the left samples may be selected with a first position offset value (denoted as F) and a stride value (denoted as S), which may depend on the measurement of the current block and the availability of adjacent blocks.

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

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

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 intercomponent prediction mode is proposed in which chroma samples are predicted with corresponding reconstructed luma samples according to a prediction model as shown in Equation 12. In Equation 12, Pred _C (x, y) denotes chroma sample prediction. α and β are two model parameters. Rec'L(x, y) are downsampled luma samples.

(12)

(12)

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

(13)

(13)

The top surrounding luminance reference samples, shaded in FIG. 11, are not downsampled by the 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.

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

3.1 Exemplary methods for up to two samples

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

(2) If top and left blocks are available, select 2 samples located at posA of the first top line and posL of the first left line. 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). 12 shows some examples of different widths and height ratios (1, 2, 4 and 8 respectively). Selected samples 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.

(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.

(5) obtain a chrominance prediction model depending on the luminance and chrominance 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 is the bit depth of the chrominance samples.

3.2 Exemplary methods for up to four samples

(1) The width-to-height ratio r is calculated from Equation 18.

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

(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.

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

3.3 Exemplary methods using lookup tables in LM acquisition

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. Note that the first entry may not be stored in the table.

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

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

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

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

Table 1: Simplified LM acquisition process

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

3.3 Method #4 up to four samples

Suppose the box width and current box height 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 luminance sampling 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 values of the four samples are used to obtain the LM parameters.

If the top block is available when the left block is not available, four chroma samples from the top block are selected 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 available, four chroma samples are taken 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 is the bit depth of the chrominance samples.

If the current mode is the 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 adjacent 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 embodiment 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 the equations that are used in the current draft VVC standard.

Input data in the process:

- intraframe prediction mode predModeIntra.

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

- variable nTbW indicating the width of the transform block,

- variable nTbH indicating the height of the transform block,

are 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:

(xTbY, yTbY) = (xTbC << 1, yTbC << 1) (8-155)

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

...

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

numSampT = availT ? ntbW : 0
numSampL = availL ? nTbH : 0 (8-156)
(8-157)

- Otherwise, the following applies:

The bCTUboundary variable is obtained as follows:

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

The 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. ...

four. ...

5. ...

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

7. 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, aboveIs4 is set to 0; otherwise set to 1.

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

- Array variables startPos[] and pickStep[] 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, 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, selectLumaPix, selectChromaPix variables are obtained as follows:

- With 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, 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:

- Variable arrays 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 change]

3.6. Another exemplary working draft on the proposed CCLM 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 of the intra-frame prediction mode.

[Add to current VVC working project as below]

The number of available adjacent chrominance samples on the top and top right numTopSamp and the number of available adjacent chrominance samples on the left and left-below 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:

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

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

- The pickStepN variable 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.

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

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

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

3. Downsampled co-located brightness samples 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 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:

- 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:

- 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:

- Otherwise, pDsY[0][y] with y = 0..nTbH − 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 adjacent left color samples pSelC[idx] are set to p[-1][pickPosL[idx]] with idx = 0..(cntL – 1), and the selected adjacent left luma 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 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] + (8-178)
pY[−3][2 * y] + pY[−3][2 * y + 1] + 4) >> 3 (8-178)

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

- variable x is set equal 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:

- 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. 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.

- 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 << (BitDepth _C − 1) (8-210)

- Otherwise, the following applies:

diff = maxY − minY (8-211)

- If diff is not equal to 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) ? ten (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)

where divSigTable[] is specified as per:

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. The 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 of exemplary embodiment]

3.7. Another exemplary working draft on the proposed CCLM 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 adjacent chromaticity samples on the top and top right numTopSamp and the number of available adjacent chromaticity samples of the left and left-bottom 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 with L and T are obtained as follows:

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

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

- The pickStepN variable 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.

The 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. Jointly allocated luma samples pY[x][y] with x = 0..nTbW * 2 − 1, y= 0..nTbH * 2 − 1 are set equal to the reconstructed luma samples prior to the deblocking filtering process at the locations (xTbY + x, yTbY + y).

2. Adjacent luma samples pY[x][y] are obtained as follows:

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

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

3. Downsampled co-located luma samples 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 apply:

- pDsY[x][y] with x = 1..nTbW − 1, y = 1..nTbH − 1 are described 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 adjacent left chrominance samples pSelC[idx] are set equal to p[-1][pickPosL[idx]] with idx = 0..(cntL – 1) and the selected adjacent left luma samples after downsampling pSelDsY [idx] with idx = 0..(cntL-1) is 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 adjacent chroma top samples pSelC[idx] are set to p[pickPosT[idx]][-1] with idx = 0..(cntT – 1), and the downsampled adjacent luminance top samples 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] 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] = 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 equal to 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) ? ten (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 like this:

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. The 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 draft for the proposed CCLM prediction

This section describes an alternative exemplary embodiment that shows other modifications that may be made in 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 adjacent chroma samples on the top and top right numTopSamp and the number of available adjacent chroma samples of 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:

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 equal to ((availT && availL && predModeIntra == INTRA_LT_CCLM) ? 0 : 1).

- variable startPosN is set equal 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.

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

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

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

3. Downsampled adjacent brightness samples 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 adjacent left chroma samples pSelC[idx] are set equal to p[-1][pickPosL[idx]] with idx = 0..(cntL – 1), and the selected adjacent left luma samples after downsampling pSelDsY[idx] with idx = 0..(cntL-1) are obtained as follows:

- variable y is 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 adjacent chroma top samples pSelC[idx] are set to p[pickPosT[idx – cntL]][-1] with idx = cntL..(cntL + cntT – 1), and the adjacent luminance top samples after downsampling pSelDsY[idx] with idx = cntL..(cntL + cntT – 1) are given 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] = 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 << (BitDepth C - 1) (8-210)

- otherwise, the following applies:

diff = maxY − minY (8-211)

- if diff is not equal to 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) ? ten (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. The 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 in 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.

18 shows a flowchart of an exemplary method for video processing. Method 1800 includes a step 1812 of determining, for converting between the current video block, which is a chroma block, and the encoded representation of the video, inter-component linear model (CCLM) parameters based on chrominance samples that are selected based on W available upper neighbor samples, W is an integer. The method 1810 further includes an act 1814 of performing a transformation based on the determination.

Figv shows a flowchart of an exemplary method for video processing. Method 1820 includes a step 1822 of determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, inter-component linear model (CCLM) prediction mode parameters based on chrominance samples that are selected based on H available left neighbor samples. current video block. The method 1820 further includes an act 1824 of performing a transformation based on the determination.

19A shows a flowchart of an exemplary method for video processing. Method 1910 includes a step 1912 of determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, inter-component linear model (CCLM) parameters based on two or four chrominance samples and/or corresponding luma samples. The method 1910 further includes an act 1914 of performing a transformation based on the determination.

19B shows a flowchart of an exemplary method for video processing. The method 1920 includes a selection step 1922 for converting between the current video block, which is a chrominance block, and the encoded representation of the video, chroma samples based on the position rule, chrominance samples used to derive inter-component linear model (CCLM) parameters. The method 1920 further includes an act 1924 of performing a transformation based on the determination. In this example, the position rule specifies to select chrominance samples that are located within the top row and/or left column of the current video block.

Figa shows a flowchart of an exemplary method for video processing. The method 2010 includes a step 2012 of determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, the positions at which the luminance samples are downsampled, in which the downsampled luminance samples are used to determine inter-component linear parameters. model (CCLM) based on chrominance samples and downsampled luminance samples, in which the downsampled luma samples are at positions corresponding to the positions of the chrominance samples that are used to derive the CCLM parameters. The method 2010 further includes a step 2024 of performing a transformation based on the definition.

Figv shows a flowchart of the sequence of operations of an exemplary method for video processing. The method 2020 includes a step 2022 of determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, a method for deriving inter-component linear model (CCLM) parameters using chrominance samples and luma samples, based on the encoding state, associated with the current video block. The method 2020 further includes a step 2024 of performing a transformation based on the definition.

20C shows a flowchart of an exemplary method for video processing. The method 2030 includes a step 2032 of determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, whether to obtain maximum and/or minimum values of the luma component and the chrominance component that are used to obtain the parameters of the inter-component linear model (CCLM) based on the availability of the left neighbor block and the top neighbor block of the current video block. The method 2030 further includes a step 2034 of performing a transformation based on the definition.

4 Example implementations of the presented technology

21A is a block diagram of a device 3000. Device 3000 may be used to implement one or more of the methods described herein. Device 3000 may be embodied in a smartphone, tablet, computer, internet of things (IoT) receiver, and so on. 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, the 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 the form of hardware circuits, some of the technologies described herein.

21B is another example of a block diagram of a video processing system in which the disclosed technologies may be implemented. 21B is a block diagram showing an exemplary video processing system 3100 in which the various methods disclosed herein may be implemented. Various implementations may include some or all of the components of system 3100. 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 multicomponent 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 techniques described herein. The encoding component 3104 may reduce the average video bit rate 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 referred to as video compression 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 bitstream (or encoded) of the video representation received at input 3102 may be used by component 3108 to generate pixel values or displayed video , which is sent to the interface 3110 display. The process of generating video for viewing by the user from a bitstream representation is sometimes referred to as video decompression. In addition, while some video processing operations are referred to as "encoding" operations or tools, it is clear that encoding tools or operations are used in the encoder and corresponding decoding tools or operations that are the reverse of the encoding to be performed by the decoder.

Examples of a peripheral bus interface or a 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 interface, IDE, and the like. The technologies described herein may be embodied in various electronic devices such as mobile phones, laptops, smartphones, or other devices that are capable of performing digital data processing and/or video.

In some embodiments, video coding 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 some embodiments may be described using the following format based on clauses.

The first set of clauses 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 converting between the current video block, which is a chrominance block, and the encoded representation of the video, inter-component linear model prediction mode parameters based on chrominance samples that are selected based on W available upper adjacent samples, W is an integer; and performing the conversion based on the determination.

2. The method of claim 1, wherein the CCLM prediction mode uses a linear mode to obtain prediction values of a chrominance component from another component.

3. The method of claim 1, wherein 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 the width of the current video block and the number of available upper right adjacent samples.

4. The method of claim 1, wherein W depends on the availability of at least one of the top neighbor or left neighbor of the current video block.

5. The method of claim 1, wherein W depends on the coding mode of the current video block.

6. The method of claim. 3, in which L has a value depending on the availability of the top right block or the top left sample, which is located next to the current block of video.

7. The method of claim 1, wherein the chrominance samples are selected based on a first position offset value (F) and a step value (S) that depend on W.

8. The method of claim 7, wherein the top left sample has 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. The method of claim 8, wherein F = W/P or F = W/P + offset, P is an integer.

10. The method of claim 9, wherein F = W >> (2 + numIs4T), wherein numIs4T is 1 if there are four adjacent samples selected within the top adjacent row and numIs4T is 0 otherwise, in where the symbol >> means the arithmetic shift of the character to the right.

11. The method of claim 7, wherein S = W Q, Q is an integer.

12. The method according to p. 7, in which S is not less than 1.

13. The method of claim 11 or 12, wherein S = Max(1, W >> (1 + numIs4T)), wherein numIs4T is 1 if there are four adjacent samples selected within the top adjacent row and numIs4T otherwise is 0, in which the symbol >> means the arithmetic shift of the character to the right.

14. The method of claim 10 or 13, wherein numIs4T is equal to 1 in the case where top neighbor samples are available, left neighbor samples are available, and the current video block is encoded with a normal CCLM that is different from the first CCLM using only left neighbor samples, and different from the second CCLM using only the top adjacent samples.

15. The method according to claim 7, wherein F = S/R, R is an integer.

16. The method of claim 7, wherein S = F/Z, Z is an integer.

17. The method according to any one of paragraphs. 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: first CCLM using only left neighbor samples, second CCLM using only top neighbor samples. , normal CCLM using both left neighbor and top neighbor samples, or modes other than first CCLM, second CCLM, and normal CCLM.

18. The method according to any one of paragraphs. 8-16, wherein at least one of Kmax, F, S, or offset is dependent on the width and/or height of the current video block.

19. The method according to any one of paragraphs. 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 paragraphs. 8-16, in which at least one of Kmax, F, S or offset depends on W.

21. A video processing method, comprising: determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, inter-component linear model (CCLM) prediction mode parameters based on chrominance samples that are selected based on H availability of left neighbors samples of the current video block; and performing the conversion based on the determination.

22. The method of claim 21, wherein the CCLM prediction mode uses a linear mode to obtain prediction values of a chrominance component from another component.

23. The method of claim 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 is 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 height of the current video block and the number of available left lower adjacent samples.

24. The method of claim 21, wherein H depends on the availability of at least one of the top neighbor or left neighbor of the current video block.

25. The method of claim 21, wherein H depends on the coding mode of the current video block.

26. The method of claim 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 block of video.

27. The method of claim 21, wherein the chrominance samples are selected based on a first position offset value (F) and a step value (S) that depend on H.

28. The method of claim 27, wherein the top left sample has coordinate (x0, y0) and the selected chrominance samples have coordinates (x0-1, y0 + F + K × S), K is an integer between 0 and kMax.

29. The method of claim 27, wherein F = H/P or F = H/P + offset, P is an integer.

30. The method according to p. 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 it is 0.

31. The method of claim 27, wherein S=H/Q, Q is an integer.

32. The method of claim 27, wherein S is at least 1.

33. The method of claim 31 or 32, wherein s = max(1, H >> (1 + numIs4L)), wherein numIs4L is 1 if there are four selected adjacent samples in the left adjacent column, and otherwise, numIs4L equals 0.

34. The method of claim 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 with a normal CCLM that is different from the first CCLM using only left neighbor samples, and different from the second CCLM using only the top neighboring samples.

35. The method of claim 27, wherein F = S R, R is an integer.

36. The method of claim 27, wherein S=F/Z, Z is an integer.

37. The method according to any one of paragraphs. 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: first CCLM using only left neighbor samples, second CCLM using only top neighbor samples. , normal CCLM using both left adjacent and top adjacent samples, or other modes other than first CCLM, second CCLM, and normal CCLM.

38. The method according to any one of paragraphs. 28-36, wherein at least one of Kmax, F, S, or offset is dependent on the width and/or height of the current video block.

39. The method according to any one of paragraphs. 28-36, in which at least one of Kmax, F, S, or offset depends on H.

40. The method according to any one of paragraphs. 28-36, wherein at least one of Kmax, F, S, or offset depends on the availability of adjacent samples.

41. The method of claim 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 claim 21, wherein in the case where left neighbor samples are not available, the selected chrominance samples have a height H regardless of whether the current video block has the first CCLM using only the top neighbor samples or not.

43. The method of claim 1, wherein 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 claim 1, wherein if no top neighbor samples are available, the selected chrominance samples are numbered W, regardless of whether the current video block has the first CCLM using only left neighbor samples or not.

45. The method according to any one of paragraphs. 1-44, wherein performing the transformation includes generating an encoded representation from the current block.

46. The method according to any one of paragraphs. 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 read-only memory with instructions, wherein the instructions, when executed by the processor, cause the processor to execute the method of any one of claims. 1-46.

48. Computer program product stored on a permanent computer-readable medium, a computer program product includes a program code for performing the method according to any one of paragraphs. 1-46.

The second set of clauses 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, for converting between the current video block, which is a chrominance block, and the encoded video representation, inter-component linear model (CCLM) parameters based on two or four chrominance samples and/or corresponding luminance samples; and performing the conversion based on the determination.

2. The method of claim 1, wherein the respective luminance samples are obtained by downsampling.

3. The method of claim 1, wherein MaxY/MaxC, MinY and MinC are first obtained and used to obtain the parameters.

4. The method according to claim 3, in which the parameters are obtained based on a 2-point hike.

5. The method of claim 3, wherein two chrominance samples are selected to obtain MaxY/MaxC and MinY/MinC, and wherein MinY is set to the smaller luma 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. The method of claim 3, wherein four chrominance samples are selected to obtain MaxY/MaxC and MinY/MinC, and wherein the four chrominance samples and corresponding luminance samples are divided into two arrays G0 and G1, each array includes two chrominance samples and their respective brightness samples.

7. The method of claim 6, wherein 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

Wherein S0, S1, S2, S3 include four chrominance samples, respectively, and further include corresponding luma samples, respectively.

8. The method of claim 7, wherein when comparing two luma sample values G0[0] and G0[1], the chrominance sample and its corresponding luminance sample in G0[0] are replaced with those in G0[1].

9. The method of claim 8, wherein the chrominance sample and its corresponding luminance sample G0[0] are replaced with the same G0[1] in case the luminance sample value G0[0] is greater than the luminance sample value G0[1] .

10. The method of claim 7, wherein when two luma sample values G1[0] and G1[1] are compared, the chrominance sample and its corresponding luminance sample in G1[0] are replaced by the same G1[1].

11. The method of claim 10, wherein the chrominance sample and its corresponding luminance sample G1[0] are replaced by the same G1[1] in the case where the luminance sample value of G1[0] is greater than the luminance sample value of G1[1] .

12. The method of claim 6, wherein when two luminance sample values G0[0] and G1[1] are compared, the chrominance samples and their corresponding luminance samples G0 are replaced by the same G1.

13. The method of claim 12, wherein the chrominance samples and their corresponding luminance samples G0 are replaced by the same G1 in the case where the luminance sample value G0[0] is greater than the luminance sample value G1[1].

14. The method of claim 7, wherein when comparing two luminance sample values G0[1] and G1[0], the chrominance sample and its corresponding luminance sample G0[1] are replaced with the same G1[0].

15. The method of claim 14, wherein the chrominance sample and its corresponding luminance sample G0[1] are replaced by the same G1[0] in the case where the luminance sample value of G0[1] is greater than the luminance sample value of G1[0] .

16. The method of claim 7, wherein when comparing two luminance sample values G0[0], G0[1], G1[0] and G1[1], subsequent replacement operations are performed selectively in the order: i) chrominance sampling operation and its corresponding luminance sample G0[0] with those of G0[1], ii) the operation of replacing the chroma sample and its corresponding luminance sample G1[0] with the same G1[1], iii) the operation of replacing the chrominance samples and their respective luminance samples G0 with the same G1 and iv) the operation of replacing a chrominance sample and its corresponding luma sample G0 [1] with the same G1 [0].

17. The method of claim 7 or 16, wherein maxY is calculated based on the sum of the luminance sample values G1[0] and G1[1] and maxC is calculated based on the sum of the luminance sample values G1[0] and G1[1].

18. The method according to claim 7 or 16, wherein maxY is calculated as the average of the luminance sample values G0[0] and G0[1] and maxC is calculated as the average of the chrominance sample values G0[0] and G0[1] or the average of the chrominance sample values G1[0] and G1[1].

19. The method according to claim 7 or 16, wherein minY is calculated based on the sum of the luminance sample values G0[0] and G0[1] and minC is calculated from the sum of the sample values G0[0] and G0[1].

20. The method of claim 7 or 16, wherein minY is calculated based on the average of the luminance sample values G0[0] and G0[1] and minC is calculated based on the chrominance sample values G0[0] and G0[1]

21. The method according to paragraphs. 17-20, wherein maxY and maxC 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], wherein the replacement operations include: i) the operation of replacing the chrominance sample and its corresponding luminance sample G1[0] with the same ones in G1[1], ii) the operation of replacing the chrominance samples and their corresponding luminance samples G0[0] or G0[1] to those of G1[0] or G1[1] and iii) the operation of replacing a chrominance sample and its corresponding luminance sample G0[1] with the same of G1[0] or iv) the operation of replacing a chrominance sample and the corresponding luminance samples G0[ 0] to G0 [1].

22. The method of claim 1, wherein if there are 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 to provide four luma samples.

23. The method of claim 22, wherein the four chroma samples include two available chroma samples and two fill chroma samples that are copied from the two available chroma samples and the four corresponding luma samples include two available luminance samples and two luminance fill samples. , which are copied from the two available brightness samples.

24. The method of claim 7, wherein S0, S1, S2, S3 are chrominance samples and the corresponding luminance samples are selected in a predetermined order within the top row and/or left column of the current video block.

25. A method for video processing, comprising: selecting, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, chrominance samples based on the position rule, chrominance samples are used to obtain inter-component linear model (CCLM) parameters; and performing a transformation based on the determination, wherein the position rule specifies to select chrominance samples that are located within the top row and/or left column of the current video block.

26. The method of claim 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 claim 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 upper neighbor samples to obtain inter-component linear model parameters, and from the second CCLM mode, which uses only left adjacent samples to obtain the parameters of the intercomponent linear model.

28. The method of claim 26, wherein the position rule specifies to select chrominance samples that are located within the top row and top right row of the current video block.

29. The method of claim 28, wherein the top row and top right row have W samples and H samples, respectively, W and H being the width and height of the current video block, respectively.

30. The method of claim 28, wherein only the available samples within the top row and top right row are selected.

31. The method of claim 28, wherein the position rule is applied to the current block of video encoded by the first CCLM mode, which uses only upper adjacent samples to obtain inter-component linear model parameters.

32. The method of claim 28, wherein the position rule is applied to the case where the top row is available and the left column is not available, and that the current video block is encoded in a normal CCLM mode that is different from the first CCLM mode, which only uses top adjacent samples to obtain parameters. CCLM, 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 according to any one of paragraphs. 26-32, in which numSampT is set based on a rule indicating that numSampT is set to nTbW in the case where top neighbor samples are available, and numSampT is set to 0 in the case when top neighbor samples are not available, and in which numSampT is the number of samples. chrominance within the upper adjacent row used to obtain the parameters of the inter-component linear model, and nTbW is the width of the current video block.

34. The method of claim 33, wherein the rule is applied to the current block of video encoded with a normal CCLM mode that differs from a first CCLM mode that uses only top neighbor samples to obtain CCLM, and from a second CCLM mode that uses only left neighbor samples. sampling to obtain the parameters of the intercomponent linear model.

35. The method according to any one of paragraphs. 26-32, in which numSampT is set based on a rule indicating that numSampT is set to nTbW + Min(numTopRight, nTbH) in case top neighbor samples are available and the current video block is encoded by a first CCLM mode that uses only top neighbor samples for get the inter-component linear model parameters and, otherwise, numSampT is set to 0 and, in which numSampT is the number of chrominance samples within the top adjacent row used to obtain the inter-component linear model parameters, nTbW and nTbH are the width and height of the current block, respectively, and numTopRight is the number of available top right adjacent samples.

36. The method of claim 25, wherein the position rule specifies to select chrominance samples that are located in the left column and lower left column of the current video block.

37. The method of claim 36, wherein the left column and 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. The method of claim 36, wherein only the available samples in the left column and lower left column are selected.

39. The method of claim 36, wherein the position rule is applied to the current block of video encoded in the second CCLM mode, which uses only left adjacent samples to obtain inter-component linear model parameters.

40. The method of claim 36, wherein the position rule is applied to the case where the top row is not available and the left column is available, and that the current block of video is encoded in a normal CCLM mode that is different from the first CCLM mode, which only uses top adjacent samples to obtain CCLM parameters, and from a second CCLM mode that uses only left adjacent samples to obtain the intercomponent linear model parameters.

41. The method according to any one of paragraphs. 36-40, wherein numSampL is set based on a rule indicating that numSampL is set to nTbH if left adjacent samples are available and otherwise, numSampL is set to 0, and wherein numSampL represents the number of chrominance samples in the left adjacent column. , used to obtain the parameters of the inter-component linear model, and nTbH is the height of the current video block.

42. The method of claim 41, wherein the rule is applied to the current block of video encoded in a normal CCLM mode that differs from a first CCLM mode that uses only top neighbor samples to obtain CCLM, and from a second CCLM mode that uses only left neighbor samples. samples to obtain CCLM.

43. The method according to any one of paragraphs. 36-40, in which numSampL is set based on a rule indicating that numSampL is set to nTbH + Min(numLeftBelow, nTbW) in the case where left neighbor samples are available and the current video block is encoded with a second CCLM mode that only uses left neighbors. samples to obtain the intercomponent linear model parameters and, otherwise, numSampL is set to 0, and where numSampL is the number of chroma samples in the left adjacent column used to obtain the intercomponent linear model parameters, nTbW and nTbH are the width and height of the current block, respectively, and numLeftBelow is the number of available lower left adjacent samples.

44. The method according to any one of paragraphs. 25-43, in which the luminance samples corresponding to the selected chrominance samples are used to derive the inter-component linear model parameters.

45. The method of claim 44, wherein the luminance samples are obtained by downsampling.

46. The method according to any one of paragraphs. 1-45, wherein performing the transformation includes generating an encoded representation from the current block.

47. The method according to any one of paragraphs. 1-45, wherein performing the transformation includes generating a current block from the encoded representation.

48. The method according to any one of paragraphs. 1-47, in which the CCLM uses downsampling co-located luma component samples to obtain chrominance component sample prediction values of the current block based on a linear model including inter-component linear model parameters.

49. An apparatus in a video system, including a processor and read-only memory with instructions, wherein the instructions, when executed by the processor, cause the processor to perform the method of any one of claims. 1-48.

50. Computer program product stored on a permanent computer-readable medium, the computer program product includes program code for performing the method according to any one of paragraphs. 1-48.

The third set of clauses 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 converting between the current video block, which is a chrominance block, and the encoded representation of the video, the positions at which the luminance samples are downsampled, in which the luminance samples after the downsampling are used to determine the parameters of the intercomponent a linear model (CCLM) based on the downsampled chroma 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 derive the CCLM parameters; and performing the transformation based on the determination.

2. The method of claim 1, wherein the luminance samples are not downsampled at a position that is outside the current video block and is not used to determine the CCLM parameters.

3. A method for video processing, comprising: determining, for converting between the current video block, which is a chrominance block, and the encoded representation of the video, a method for obtaining intercomponent linear model (CCLM) parameters using chrominance samples and luminance samples based on the coding state , associated with the current video block; and performing the conversion based on the determination.

4. The method of claim 3, wherein the encoding state corresponds to the color format of the current video block.

5. The method of claim 4, wherein the color format is 4:2:0 or 4:4:4.

6. The method of claim 3, wherein the encoding condition corresponds to the color representation method of the current video block.

7. The method of claim 6, wherein the color representation method is RGB or YCbCr.

8. The method of claim 3, wherein the chrominance samples are downsampled and the determination depends on the locations of the downsampled chrominance samples.

9. The method of claim 3, wherein the method for obtaining the parameters comprises determining CCLM parameters based on chrominance samples and luma samples that are selected from a group of adjacent chrominance samples based on a position rule.

10. The method of claim 3, wherein the method for obtaining the parameters comprises determining the CCLM parameters based on the maximum and minimum values of the chrominance samples and the luma samples.

11. The method of claim 3, wherein the method for obtaining the parameters comprises determining CCLM parameters that are entirely determined by two chrominance samples and corresponding two luma samples.

12. The method of claim 3, wherein the method for obtaining the parameters comprises determining the CCLM parameters using a parameter table whose entries are obtained according to two chrominance sample values and two luma sample values.

13. A method for video processing, comprising: determining, for converting between the current video block, which is a chrominance block, and the encoded video representation, whether to obtain the maximum values and/or minimum values of the luminance component and the chrominance component used to obtain the parameters of the intercomponent a linear model (CCLM), based on the availability of the left neighbor block and the top neighbor block of the current video block; and performing the transformation based on the determination.

14. The method of claim 13, wherein the maximum values and/or minimum values are not obtained if the left neighbor block and the top neighbor block are not available.

15. The method of claim 13, wherein determining the definitions based on the number of available adjacent samples of the current video block, and wherein the available adjacent samples are used to derive inter-component linear model parameters.

16. The method of claim 15, wherein no maximum values and/or minimum values are obtained in the case of numSampL == 0 and numSampT == 0, numSampL and numSampT indicate the number of available neighbor samples from the left neighbor block and the number of available neighbor samples from the top block, respectively, and in which the available neighbor samples from the left neighbor block and the available neighbor samples from the top neighbor block are used to obtain the intercomponent linear model parameters.

17. The method of claim 15, wherein no maximum values and/or minimum values are obtained in the case of numSampL + numSampT == 0, numSampL and numSampT indicate the number of available neighbor samples from the left neighbor block and the number of available neighbor samples from the top neighbor block, respectively, and in which the available neighbor samples from the left neighbor block and the available neighbor samples from the top neighbor block are used to derive the intercomponent linear model parameters.

18. The method according to any one of paragraphs. 1-17, wherein performing the transformation includes generating an encoded representation from the current block.

19. The method according to any one of paragraphs. 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 read-only memory with instructions, wherein the instructions, when executed by the processor, cause the processor to execute the method of any one of claims. 1-19.

21. Computer program product stored on a permanent computer-readable medium, the computer program product includes program code for performing the method according to any one of paragraphs. 1-19.

The fourth set of clauses describes specific features and aspects of the disclosed technologies listed in the preceding section.

1. A video processing method, comprising: determining for a current video block that contains a chrominance block and is based on two or more chrominance samples, a set of linear model parameter values in which two or more chrominance samples are selected from a group of adjacent chrominance samples into a chrominance block, and construction based on the linear model of the current video block.

2. The method of claim 1, wherein the top-left chroma block sample is (x, y), wherein the chroma block width and height are W and H, respectively, and in that the group of adjacent chrominance samples comprises:

Sample A 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 claim 2, wherein the upper left adjacent block and the aforementioned adjacent block of the current video block are available, and wherein the two or more chrominance samples comprise A, D, J, and M samples.

4. The method of claim 2, wherein the top left adjacent block of the current video block is available, and wherein two or more chrominance samples contain samples A and D.

5. The method of claim 2, wherein the top adjacent block of the current video block is available, and wherein two or more chrominance samples contain J and M samples.

6. A video processing method, comprising: generating for the current video block, which contains the chrominance block, a plurality of groups containing samples of the chrominance and brightness of the neighboring block of the current video block; determining, based on the plurality of groups, maximum and minimum values, a set of values for the parameters of the linear model; and reconstructing based on the linear model of the current video block.

7. The method of claim 6, wherein generating the plurality of groups is based on the availability of a neighboring block of the current video block.

8. The method according to claim 6, wherein the plurality of groups are S0 and S1, wherein the maximum luminance value is calculated as maxL = f1(maxL _S0 , maxL _S1 ,…, maxL _Sm , where f1 is the first function and maxL _Si is the maximum the brightness value of the group Si of the set of groups, in which the maximum chromaticity value is calculated as maxC = f2(maxC _S0 , maxC _S1 ,…, maxC _Sm , where f2 is the second function, maxC _Si is the maximum chromaticity value of the group Si, in which the minimum luminance value is calculated as minL = f3(minL _S0 , minL _S1 ,…, minL _Sm ) where f3 is the third function and minL _Si is the minimum luminance value of the Si group, where the minimum chromaticity value is calculated as minC = f4(minC _S0 , minC _S1 ,…, minC _Sm ) where f4 is the fourth function and minC _Si is the maximum chromaticity value from the group Si, and where the linear model parameters Contains α and β which are calculated as α = ( maxC − minC) / (maxL − minL) and β = minC − α×minL.

9. The method of claim 8, wherein the top left chrominance block sample is (x, y), wherein the chroma block width and height are W and H, respectively, and wherein the group of adjacent chrominance samples comprises.

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 according to claim 9, in which the upper left adjacent block and the upper block of the current video block are available, in which the maximum luma and chrominance values and the minimum luminance and chrominance values for the group S0 (maxL _S0 , maxC _S0 , minL _S0 and minL _S0 respectively ) are based 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 claim 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 claim 9, wherein an upstream block of the current video block is available, and wherein maxL, maxC, minL and minC are based on J and M samples.

13. The method according to claim 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 chrominance sample.

14. The method of claim 6, wherein generating the plurality of groups is based on the height or width of the current video block.

15. Method for video processing, comprising:

generating downsampled luma and chrominance samples by downsampling the luminance and chrominance samples of a neighboring block of the current video block with height (H) and width (W);

determining, based on downsampled luma and chrominance samples, a set of values for the linear model parameters for the current video block; and

restoration, based on a linear model, of the current video block.

16. The method of claim 15 wherein the downsampling is based on height or width.

17. The method according to p. 16, in which W < H.

18. The method according to claim 16, where W > H.

19. The method of claim 15, wherein the top left sample of the current video block is R[0, 0], wherein the downsampled chrominance samples comprise R[-1, k×H/W] samples, and where K is a non-negative integer a number from 0 to W-1.

20. The method of claim 15, wherein the top left sample of the current video block is R[0, 0], wherein the downsampled chrominance samples comprise R[K × H/W, −1] samples, and K is a non-negative integer number from 0 to H-1.

21. The method of claim 15, wherein the refinement process is performed on the downsampled luminance 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 claim 21, wherein the refinement process comprises a filtering process.

23. The method of claim 21, wherein the refinement process comprises a non-linear process.

24. The method of 15, wherein the linear model parameters are α and β, wherein α = (C1−C0) / (L1−L0) and β = C0 − αL0, where C0 and C1 are chrominance samples, and wherein L0 and L1 are brightness samples.

25. The method of claim 24, wherein C0 and L0 are based on S downsampled luminance and chrominance samples, denoted {Lx1, Lx2, ..., LxS} and {Cx1, Cx2, ..., CxS}, respectively, where C1 and L1 are based on T downsampled luminance and chrominance samples, denoted {Ly1, Ly2, ..., LyT} and {Cy1, Cy2, ..., CyT}, respectively,

when C0 = f0(Cx1, Cx2, …, CxS), L0 = f1(Lx1, Lx2, …, LxS), C1 = f2(Cy1, Cy2, …, CyT) and L1 = f1(Ly1, Ly2, …, LyT), and

where f0, f1, f2 and f3 are functions.

26. The method of claim 25, wherein f0 and f1 are the first function.

27. The method of claim 25, wherein f2 and f3 are the second function.

28. The method of claim 25, wherein f0, f1, f2, and f3 are the third function.

29. The method of claim 28, wherein the third function is an averaging function.

30. The method according to claim 25, in which S = T.

31. The method of claim 25, wherein {lx1, lx2, ..., lxs} are minimum samples of the group of luma samples.

32. The method of claim 25, wherein {lx1, lx2, ..., lxs} are the largest samples of the group of luma samples.

33. The method of claim 31 or 32, wherein the luminance sample group contains all adjacent samples used in VTM-3.0 to derive the linear model parameters.

34. The method of claim 31 or 32, wherein the luminance sample group comprises a subset of adjacent samples used in VTM-3.0 to derive the linear model parameters, and wherein the subset excludes all adjacent samples.

35. The method of claim 1, wherein two or more chrominance 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 claim 1, wherein the 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 claim 1, wherein two or more chrominance block samples are selected based on the coding mode of the current video block.

38. The method of claim 37, wherein the encoding mode of the current video block is a first linear mode that is different from a second linear mode that only uses left adjacent samples, and a third linear mode that uses only upper adjacent samples in which the coordinates of the top the left samples 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 claim 38, wherein the two or more chrominance 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 claim 38, wherein the two or more chrominance samples contain 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 claim 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 claim 38, wherein the two or more chrominance samples comprise 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 claim 38, wherein the two or more chroma samples comprise 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 claim 38, wherein the two or more chrominance samples comprise 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 claim 38, wherein the two or more chrominance samples contain 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 claim 38, wherein the two or more chroma samples comprise samples with coordinates (x, y-1), (x + (2w) / 4, y-1), (x + 3 * 2W) / 4, y - 1) and (x + (2w) -1, y-1).

47. The method of claim 38, wherein the two or more chroma samples comprise 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 claim 38, wherein the two or more chroma samples comprise 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 claim 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 claim 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 according to any one of paragraphs. 39-50, in which exactly two of the four samples are selected to determine a set of values for the linear model parameters.

52. The method according to any one of paragraphs. 1-51.

53. Device for encoding video containing a processor configured to perform the method according to any one of paragraphs. 1-51.

54. A device in a video system, comprising a processor and 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 claims. 1-51.

55. Computer program product stored on a permanent computer-readable medium, the computer program product includes program code for performing the method according to any one of paragraphs. 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 implemented in various systems, digital electronic circuitry, or computer software, firmware, or hardware, including 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 as one or more computer program products, i. one or more modules of computer program instructions, encoded on a tangible and permanent computer-readable medium, for executing or controlling an 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 transmitted signal, or a combination of one or more of them. The term "data processing unit" or "data processing device" encompasses all data processing devices, appliances, and machines, including by way of example a programmable processor, a computer, or a plurality of processors or computers. In addition to hardware, the device may include code that generates the conditions for executing said computer program, such as code that generates a 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) may be written in any form of a programming language, including compiled or interpreted languages, and may be deployed in any form, including as a standalone 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 in a file system. A program may be stored in a portion 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 several coordinated files (for example, files that store one or more multiple 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 inputs and generate outputs. 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 Specific 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, a processor receives instructions and data from read-only memory or random access memory, or both. The main elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include, or be operatively connected 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 must not have such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of read-only memory, memory devices and information, including, by way of example, semiconductor memory devices such as EPROM, EEPROM, and flash memory devices. The processor and memory may be supplemented or incorporated into the system with special purpose logic.

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" encompasses the meaning of "and/or" unless the context clearly indicates otherwise.

This patent document contains many distinctive features, but they should not be construed as limiting 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 separate embodiments may also be implemented in combination in one embodiment. Conversely, various features that are described in the context of one embodiment may also be implemented in multiple embodiments alone or in any suitable subcombination. Moreover, although the previously described features may be considered to work in certain combinations and, even initially claimed as such, one or more features from the claimed combination may, in some cases, be excluded from the combination, and the claimed combination can be used as a subcombination. or subcombination changes.

Likewise, while the drawings show the operations in a specific order, this order should not be construed as being required to perform such operations, as a specified order, or that all the illustrated operations must be performed to obtain the required results. Moreover, the separation of the various components of the system in the embodiments described in this patent document should not be understood as a required separation in all embodiments.

Only a few implementations and examples are described, and other implementations, improvements and variations can be made based on the description and drawings, which are given in this patent document.

Claims (38)

1. A method for encoding video data, comprising the steps of: determine, for conversion between the current video video block, which is a chrominance block, and the encoded video stream, intercomponent linear model (CCLM) parameters based on maxY, maxC, minY, and minC, where maxY, maxC, minY, and minC are derived from two or four indicators, and the indicator has a display with a sample of color and a corresponding sample of brightness; and performing a transformation based on the determination; and applying, in response to mapping two chrominance samples and two corresponding luminance samples with two original metrics used to obtain maxY, maxC, minY and minC, a padding operation to generate two filled chrominance samples and two filled luminance samples. 2. The method of claim 1, wherein the corresponding luminance samples are obtained by downsampling in the case where the color format of the current video block is 4:2:0 or 4:2:2, and the corresponding luminance samples are obtained without downsampling in the case where the color format of the current video block is 4:4:4. 3. The method of claim 1, wherein said two raw metrics are designated as S0 and S1, and the two mapped metrics with which two filled chrominance samples and two filled luma samples are displayed are designated as S2 and S3, wherein the filling operation is performed in the following order: i) the chrominance sample and the corresponding luma sample mapped with S0 are copied as the chroma sample and the corresponding luma sample mapped with S3, respectively; ii) the chrominance sample and the corresponding luma sample mapped from S1 are copied as the chroma sample and the corresponding luma sample mapped from S2, respectively; iii) the chroma sample and the corresponding luma sample mapped with S1 are copied as the chroma sample and the corresponding luma sample mapped with S0, respectively; iv) The chrominance sample and the corresponding luma sample mapped from S3 are copied as the chroma sample and the corresponding luma sample mapped from S1, respectively. 4. The method according to claim 1 or 2, wherein maxY is equal to or greater than one of the two luminance samples displayed with two initial indices, maxC is equal to the chrominance sample corresponding to the largest luminance sample, minY is equal to or less than one of the two luma samples displayed with two initial indices , and minC is equal to the chrominance sample corresponding to the smallest luma sample. 5. The method of claim 1 or 2, wherein, in response to using four chrominance samples and four corresponding luminance samples mapped to four metrics to obtain maxY, maxC, minY, and minC, the four metrics are divided into two arrays G0 and G1, wherein each array contains two indicators. 6. The method of claim 5, wherein G0[0]=S0, G0[1]=S2, G1[0]=S1 b G1[1]=S3, wherein S0, S1, S2, and S3 are each one metric displayed with a chroma sample and a corresponding luma sample. 7. The method of claim 6, further comprising applying a first comparison between luminance samples G0[0] and luminance samples G0[1] and selectively swapping G0[0] and G0[1] based on the first comparison. 8. The method of claim 7, further comprising performing a permutation between G0[0] and G0[1] in response to the luminance sample G0[0] being larger than the luminance sample G0[1]. 9. The method according to claim 7 or 8, further comprising applying a second comparison between the luminance samples G1[0] and the luminance samples G1[1] after the first comparison, and selectively swapping G1[0] and G1[1], by basis of the second comparison. 10. The method of claim 9, further comprising performing a permutation between G1[0] and G1[1] in response to the G1[0] luminance sample being greater than the G1[1] luminance sample. 11. The method of claim 9 or 10, further comprising the steps of applying a third comparison between the luminance samples G0[0] and the luminance samples G1[1] after the second comparison, and selectively swapping G0 and G1 based on the third comparison, wherein the step the permutation of G0 and G1 contains substeps in which G0[0] and G1[0] are permuted and G0[1] and G1[1] are permuted. 12. The method of claim 11, further comprising performing a permutation between G0 and G1 in response to the luminance sample G0[0] being larger than the luminance sample G1[1]. 13. The method of claim 11 or 12, further comprising applying a fourth comparison between luminance samples G0[1] and luminance samples G1[0] after the third comparison, and selectively swapping G0[1] and G1[0] by the basis of the fourth comparison. 14. The method of claim 13, further comprising performing a permutation between G0[1] and G1[0] in response to the luminance sample G0[1] being greater than the luminance sample G1[0]. 15. The method according to claim 13 or 14, further comprising obtaining maxY based on the average of the luminance samples G1[0] and G1[1] and maxC based on the average of the chrominance samples G1[0] and G1[1] after the fourth comparison. 16. The method according to claim 13 or 14, further comprising obtaining minY based on the average of the luminance samples G0[0] and G0[1] and minC based on the average of the chrominance samples G0[0] and G0[1] after the fourth comparison. 17. The method according to any one of claims 1-16, wherein the transformation includes encoding the current block of video into a bitstream. 18. The method of any one of claims 1-16, wherein the transformation includes decoding the current block of video from the bitstream. 19. A video data encoding device containing a processor and a read-only memory storing instructions that cause, when executed by the processor, the execution by the processor: determining, for converting between the current video video block, which is a chrominance block, and the encoded video stream, intercomponent linear model (CCLM) parameters based on maxY, maxC, minY, and minC, where maxY, maxC, minY, and minC are derived from two or four indicators, and the indicator has a display with a sample of color and a corresponding sample of brightness; and transformations based on the definition; and applying, in response to displaying two chrominance samples and two corresponding luminance samples with two raw metrics used to obtain maxY, maxC, minY, and minC, a padding operation to generate two filled chrominance samples and two filled luminance samples. 20. The apparatus of claim 19, wherein the corresponding luminance samples are obtained by downsampling in the case where the color format of the current video block is 4:2:0 or 4:2:2, and the corresponding luminance samples are obtained without downsampling in the case where the color format of the current video block is 4:4:4. 21. A machine-readable storage medium that stores instructions that cause the processor to execute: determining, for converting between the current video video block, which is a chrominance block, and the encoded video stream, intercomponent linear model (CCLM) parameters based on maxY, maxC, minY, and minC, where maxY, maxC, minY, and minC are derived from two or four indicators, and the indicator has a display with a sample of color and a corresponding sample of brightness; and transformations based on the definition; and applying, in response to displaying two chrominance samples and two corresponding luminance samples with two raw metrics used to obtain maxY, maxC, minY, and minC, a padding operation to generate two filled chrominance samples and two filled luminance samples. 22. A computer-readable storage medium that stores a video bitstream generated by a video data processing device by executing a method comprising the steps of: determine, for conversion between the current video video block, which is a chrominance block, and the encoded video stream, intercomponent linear model (CCLM) parameters based on maxY, maxC, minY, and minC, where maxY, maxC, minY, and minC are derived from two or four indicators, and the indicator has a display with a sample of color and a corresponding sample of brightness; and performing a transformation based on the determination; and applying, in response to mapping two chrominance samples and two corresponding luminance samples with two original metrics used to obtain maxY, maxC, minY and minC, a padding operation to generate two filled chroma samples and two filled luminance samples.

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