EP4695980A1

EP4695980A1 - Method and apparatus of alf adaptive parameters for video coding

Info

Publication number: EP4695980A1
Application number: EP24787885.3A
Authority: EP
Inventors: Shih-Chun Chiu; Ching-Yeh Chen
Original assignee: Mediatek Inc; MediaTek Inc
Current assignee: Mediatek Inc; MediaTek Inc
Priority date: 2023-04-10
Filing date: 2024-03-21
Publication date: 2026-02-18
Also published as: CN120693861A; TW202441952A; WO2024212779A1

Abstract

Method and apparatus for video coding using adaptive parameter for ALF classifiers. According to this method, reconstructed pixels are received, wherein the reconstructed pixels comprise a current block. One or more parameters for an ALF classifier are determined according to coding information associated with the current block or one or more statistical values of samples in a region. The ALF classifier, with a parameter set including said one or more parameters derived, is applied to target data associated with the current block to determine an ALF index. A target ALF is selected from an ALF set according to the ALF index. The target ALF is applied to the current block to generate filtered-reconstructed current block. The filtered-reconstructed current block is provided.

Description

METHOD AND APPARATUS OF ALF ADAPTIVE PARAMETERS FOR VIDEO CODING

CROSS REFERENCE TO RELATED APPLICATIONS
The present invention is a non-Provisional Application of and claims priority to U.S. Provisional Patent Application No. 63/495,135, filed on April 10, 2023. The U.S. Provisional Patent Application is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates to video coding system using ALF (Adaptive Loop Filter) . In particular, the present invention discloses adaptive parameters for ALF classifier to improve the performance of ALF processing.
BACKGROUND AND RELATED ART
Versatile video coding (VVC) is the latest international video coding standard developed by the Joint Video Experts Team (JVET) of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) . The standard has been published as an ISO standard: ISO/IEC 23090-3: 2021, Information technology -Coded representation of immersive media -Part 3: Versatile video coding, published Feb. 2021. VVC is developed based on its predecessor HEVC (High Efficiency Video Coding) by adding more coding tools to improve coding efficiency and also to handle various types of video sources including 3-dimensional (3D) video signals.
Fig. 1A illustrates an exemplary adaptive Inter/Intra video encoding system incorporating loop processing. For Intra Prediction 110, the prediction data is derived based on previously coded video data in the current picture. For Inter Prediction 112, Motion Estimation (ME) is performed at the encoder side and Motion Compensation (MC) is performed based on the result of ME to provide prediction data derived from other picture (s) and motion data. Switch 114 selects Intra Prediction 110 or Inter-Prediction 112 and the selected prediction data is supplied to Adder 116 to form prediction errors, also called residues. The prediction error is then processed by Transform (T) 118 followed by Quantization (Q) 120. The transformed and quantized residues are then coded by Entropy Encoder 122 to be included in a video bitstream corresponding to the compressed video data. The bitstream associated with the transform coefficients is then packed with side information such as motion and coding modes associated with Intra prediction and Inter prediction, and other information such as parameters associated with loop filters applied to underlying image area. The side information associated with Intra Prediction 110, Inter prediction 112 and in-loop filter 130, are provided to Entropy Encoder 122 as shown in Fig. 1A. When an Inter-prediction mode is used, a reference picture or pictures have to be reconstructed at the encoder end as well. Consequently, the transformed and quantized residues are processed by Inverse Quantization (IQ) 124 and Inverse Transformation (IT) 126 to recover the residues. The residues are then added back to prediction data 136 at Reconstruction (REC) 128 to reconstruct video data. The reconstructed video data may be stored in Reference Picture Buffer 134 and used for prediction of other frames.
As shown in Fig. 1A, incoming video data undergoes a series of processing in the encoding system. The reconstructed video data from REC 128 may be subject to various impairments due to a series of processing. Accordingly, in-loop filter 130 is often applied to the reconstructed video data before the reconstructed video data are stored in the Reference Picture Buffer 134 in order to improve video quality. For example, deblocking filter (DF) , Sample Adaptive Offset (SAO) and Adaptive Loop Filter (ALF) may be used. The loop filter information may need to be incorporated in the bitstream so that a decoder can properly recover the required information. Therefore, loop filter information is also provided to Entropy Encoder 122 for incorporation into the bitstream. In Fig. 1A, Loop filter 130 is applied to the reconstructed video before the reconstructed samples are stored in the reference picture buffer 134. The system in Fig. 1A is intended to illustrate an exemplary structure of a typical video encoder. It may correspond to the High Efficiency Video Coding (HEVC) system, VP8, VP9, H. 264 or VVC.
The decoder, as shown in Fig. 1B, can use similar or portion of the same functional blocks as the encoder except for Transform 118 and Quantization 120 since the decoder only needs Inverse Quantization 124 and Inverse Transform 126. Instead of Entropy Encoder 122, the decoder uses an Entropy Decoder 140 to decode the video bitstream into quantized transform coefficients and needed coding information (e.g. ILPF information, Intra prediction information and Inter prediction information) . The Intra prediction 150 at the decoder side does not need to perform the mode search. Instead, the decoder only needs to generate Intra prediction according to Intra prediction information received from the Entropy Decoder 140. Furthermore, for Inter prediction, the decoder only needs to perform motion compensation (MC 152) according to Inter prediction information received from the Entropy Decoder 140 without the need for motion estimation.
According to VVC, an input picture is partitioned into non-overlapped square block regions referred as CTUs (Coding Tree Units) , similar to HEVC. Each CTU can be partitioned into one or multiple smaller size coding units (CUs) . The resulting CU partitions can be in square or rectangular shapes. Also, VVC divides a CTU into prediction units (PUs) as a unit to apply prediction process, such as Inter prediction, Intra prediction, etc.
Adaptive Loop Filter in VVC
In VVC, an Adaptive Loop Filter (ALF) with block-based filter adaption is applied. For the luma component, one filter is selected among 25 filters for each 4×4 block, based on the direction and activity of local gradients.
Filter shape
Two diamond filter shapes (as shown in Fig. 2) are used. The 7×7 diamond shape 220 is applied for luma component and the 5×5 diamond shape 210 is applied for chroma components.
Block classification
For luma component, each 4×4 block is categorized into one out of 25 classes. The classification index C is derived based on its directionality D and a quantized value of activityas follows:
To calculate D andgradients of the horizontal, vertical and two diagonal direction are first calculated using 1-D Laplacian:
where indices i and j refer to the coordinates of the upper left sample within the 4×4 block and R (i, j) indicates a reconstructed sample at coordinate (i, j) .
To reduce the complexity of block classification, the subsampled 1-D Laplacian calculation is applied to the vertical direction (Fig. 3A) and the horizontal direction (Fig. 3B) . As shown in Figs. 3C-D, the same subsampled positions are used for gradient calculation of all directions (g_d1 in Fig. 3C and g_d2 in Fig. 3D) .
Then D maximum and minimum values of the gradients of horizontal and vertical directions are set as:
The maximum and minimum values of the gradient of two diagonal directions are set as:
To derive the value of the directionality D, these values are compared against each other and with two thresholds t₁ and t₂:
Step 1. If bothandare true, D is set to 0.
Step 2. Ifcontinue from Step 3; otherwise continue from Step 4.
Step 3. IfD is set to 2; otherwise D is set to 1.
Step 4. IfD is set to 4; otherwise D is set to 3.
The activity value A is calculated as:
A is further quantized to the range of 0 to 4, inclusively, and the quantized value is denoted as
For chroma components in a picture, no classification is applied.
Geometric transformations of filter coefficients and clipping values
Before filtering each 4×4 luma block, geometric transformations such as rotation or diagonal and vertical flipping are applied to the filter coefficients f (k, l) and to the corresponding filter clipping values c (k, l) depending on gradient values calculated for that block. This is equivalent to applying these transformations to the samples in the filter support region. The idea is to make different blocks to which ALF is applied more similar by aligning their directionality.
Three geometric transformations, including diagonal, vertical flip and rotation are introduced:
Diagonal: f_D (k, l) =f (l, k) , c_D (k, l) =c (l, k) ,
Vertical flip: f_V (k, l) =f (k, K-l-1) , c_V (k, l) =c (k, K-l-1) ,
Rotation: f_R (k, l) =f (K-l-1, k) , c_R (k, l) =c (K-l-1, k) ,
where K is the size of the filter and 0≤k, l≤K-1 are coefficients coordinates, such that location (0, 0) is at the upper left corner and location (K-1, K-1) is at the lower right corner. The transformations are applied to the filter coefficients f (k, l) and to the clipping values c (k, l) depending on gradient values calculated for that block. The relationship between the transformation and the four gradients of the four directions are summarized in the following table.
Table 1. Mapping of the gradient calculated for one block and the transformations
Filtering process
At decoder side, when ALF is enabled for a CTB, each sample R (i, j) within the CU is filtered, resulting in sample value R′ (i, j) as shown below,
where f (k, l) denotes the decoded filter coefficients, K (x, y) is the clipping function and c (k, l) denotes the decoded clipping parameters. The variable k and l varies between –L/2 and L/2, where L denotes the filter length. The clipping function K (x, y) =min (y, max (-y, x) ) which corresponds to the function Clip3 (-y, y, x) . The clipping operation introduces non-linearity to make ALF more efficient by reducing the impact of neighbour sample values that are too different with the current sample value.
Cross Component Adaptive Loop Filter
CC-ALF uses luma sample values to refine each chroma component by applying an adaptive, linear filter to the luma channel and then using the output of this filtering operation for chroma refinement. Fig. 4A provides a system level diagram of the CC-ALF process with respect to the SAO, luma ALF and chroma ALF processes. As shown in Fig. 4A, each colour component (i.e., Y, Cb and Cr) is processed by its respective SAO (i.e., SAO Luma 410, SAO Cb 412 and SAO Cr 414) . After SAO, ALF Luma 420 is applied to the SAO-processed luma and ALF Chroma 430 is applied to SAO-processed Cb and Cr. However, there is a cross-component term from luma to a chroma component (i.e., CC-ALF Cb 422 and CC-ALF Cr 424) . The outputs from the cross-component ALF are added (using adders 432 and 434 respectively) to the outputs from ALF Chroma 430.
Filtering in CC-ALF is accomplished by applying a linear, diamond shaped filter (e.g. filters 440 and 442 in Fig. 4B) to the luma channel. In Fig. 4B, a blank circle indicates a luma sample and a dot-filled circle indicate a chroma sample. One filter is used for each chroma channel, and the operation is expressed as:
where (x, y) is chroma component i location being refined, (x_Y, y_Y) is the luma location based on (x, y) , S_i is filter support area in luma component, and c_i (x₀, y₀) represents the filter coefficients.
As shown in Fig, 4B, the luma filter support is the region collocated with the current chroma sample after accounting for the spatial scaling factor between the luma and chroma planes.
In the VVC reference software, CC-ALF filter coefficients are computed by minimizing the mean square error of each chroma channel with respect to the original chroma content. To achieve this, the VTM (VVC Test Model) algorithm uses a coefficient derivation process similar to the one used for chroma ALF. Specifically, a correlation matrix is derived, and the coefficients are computed using a Cholesky decomposition solver in an attempt to minimize a mean square error metric. In designing the filters, a maximum of 8 CC-ALF filters can be designed and transmitted per picture. The resulting filters are then indicated for each of the two chroma channels on a CTU basis.
Additional characteristics of CC-ALF include:
● The design uses a 3x4 diamond shape with 8 taps.
● Seven filter coefficients are transmitted in the APS.
● Each of the transmitted coefficients has a 6-bit dynamic range and is restricted to power-of-2 values.
● The eighth filter coefficient is derived at the decoder such that the sum of the filter coefficients is equal to 0.
● An APS may be referenced in the slice header.
● CC-ALF filter selection is controlled at CTU-level for each chroma component
● Boundary padding for the horizontal virtual boundaries uses the same memory access pattern as luma ALF.
As an additional feature, the reference encoder can be configured to enable some basic subjective tuning through the configuration file. When enabled, the VTM attenuates the application of CC-ALF in regions that are coded with high QP and are either near mid-grey or contain a large amount of luma high frequencies. Algorithmically, this is accomplished by disabling the application of CC-ALF in CTUs where any of the following conditions are true:
● The slice QP value minus 1 is less than or equal to the base QP value.
● The number of chroma samples for which the local contrast is greater than (1 << (bitDepth –2 ) ) –1 exceeds the CTU height, where the local contrast is the difference between the maximum and minimum luma sample values within the filter support region.
● More than a quarter of chroma samples are in the range between (1 << (bitDepth –1 ) ) –16 and (1 << (bitDepth –1 ) ) + 16
The motivation for this functionality is to provide some assurance that CC-ALF does not amplify artefacts introduced earlier in the decoding path (This is largely due the fact that the VTM currently does not explicitly optimize for chroma subjective quality) . It is anticipated that alternative encoder implementations may either not use this functionality or incorporate alternative strategies suitable for their encoding characteristics.
Filter parameters signalling
ALF filter parameters are signalled in Adaptation Parameter Set (APS) . In one APS, up to 25 sets of luma filter coefficients and clipping value indexes, and up to eight sets of chroma filter coefficients and clipping value indexes can be signalled. To reduce bits overhead, filter coefficients of different classification for luma component can be merged. In slice header, the indices of the APSs used for the current slice are signalled.
Clipping value indexes, which are decoded from the APS, allow determining clipping values using a table of clipping values for both luma and Chroma components. These clipping values are dependent of the internal bitdepth. More precisely, the clipping values are obtained by the following formula:
AlfClip= {round (2^B-α^*n ) for n∈ [0.. N-1] }
with B equal to the internal bitdepth, α is a pre-defined constant value equal to 2.35, and N equal to 4 which is the number of allowed clipping values in VVC. The AlfClip is then rounded to the nearest value with the format of power of 2.
In slice header, up to 7 APS indices can be signalled to specify the luma filter sets that are used for the current slice. The filtering process can be further controlled at CTB level. A flag is always signalled to indicate whether ALF is applied to a luma CTB. A luma CTB can choose a filter set among 16 fixed filter sets and the filter sets from APSs. A filter set index is signalled for a luma CTB to indicate which filter set is applied. The 16 fixed filter sets are pre-defined and hard-coded in both the encoder and the decoder.
For the chroma component, an APS index is signalled in slice header to indicate the chroma filter sets being used for the current slice. At CTB level, a filter index is signalled for each chroma CTB if there is more than one chroma filter set in the APS.
The filter coefficients are quantized with norm equal to 128. In order to restrict the multiplication complexity, a bitstream conformance is applied so that the coefficient value of the non-central position shall be in the range of -2⁷ to 2⁷ -1, inclusive. The central position coefficient is not signalled in the bitstream and is considered as equal to 128.
Adaptive Loop Filter in ECM
In ECM7 (Muhammed Coban, et al., “Algorithm description of Enhanced Compression Model 7 (ECM 7) ” , Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29) , 28th Meeting, Mainz, DE, 20–28 October 2022, Document: JVET-AB2025) , some changes from the VVC ALF are disclosed. A brief overview is shown below.
ALF simplification
ALF gradient subsampling and ALF virtual boundary processing are removed. Block size for classification is reduced from 4x4 to 2x2. Filter size for both luma and chroma, for which ALF coefficients are signalled, is increased to 9x9.
ALF with fixed filters
To filter a luma sample, three different classifiers (C₀, C₁ and C₂) and three different sets of filters (F₀, F₁ and F₂) are used. Sets F₀ and F₁ contain fixed filters, with coefficients trained for classifiers C₀ and C₁. Coefficients of filters in F₂ are signalled. Which filter from a set F_i is used for a given sample is decided by a class C_i assigned to this sample using classifier C_i.
Filtering
At first, two 13x13 diamond shape fixed filters F₀ and F₁ are applied to derive two intermediate samples R₀ (x, y) and R₁ (x, y) . After that, F₂ is applied to R₀ (x, y) , R₁ (x, y) , and neighbouring samples to derive a filtered sample as
where f_i, j is the clipped difference between a neighbouring sample and current sample R (x, y) and g_i is the clipped difference between R_i-20 (x, y) and current sample. The filter coefficients c_i, i=0, …21, are signalled.
Classification
Based on directionality D_i and activityaclass C_i is assigned to each 2x2 block:
where M_D, i represents the total number of directionalities D_i.
As in VVC, values of the horizontal, vertical, and two diagonal gradients are calculated for each sample using 1-D Laplacian. The sum of the sample gradients within a 4×4 window that covers the target 2×2 block is used for classifier C₀ and the sum of sample gradients within a 12×12 window is used for classifiers C₁ and C₂. The sums of horizontal, vertical and two diagonal gradients are denoted, respectively, asandThe directionality D_i is determined by comparing
with a set of thresholds. The directionality D₂ is derived as in VVC using thresholds 2 and 4.5. For D₀ and D₁, horizontal/vertical edge strengthand diagonal edge strengthare calculated first. Thresholds Th= [1.25, 1.5, 2, 3, 4.5, 8] are used. Edge strengthis 0 if otherwise, is the maximum integer such thatEdge strengthis 0 ifotherwise, is the maximum integer such that Wheni.e., horizontal/vertical edges are dominant, the D_i is derived by using Table 2A; otherwise, diagonal edges are dominant, the D_i is derived by using Table 2B.
Table 2A. Mapping ofandto D_i
Table 2B. Mapping ofandto D_i
To obtainthe sum of vertical and horizontal gradients A_i is mapped to the range of 0 to n, where n is equal to 4 forand 15 forand
In an ALF_APS, up to 4 luma filter sets are signalled, each set may have up to 25 filters.
Alternative 2x2 ALF Classifier
Classification in ALF is extended with an additional alternative classifier. For a signalled luma filter set, a flag is signalled to indicate whether the alternative classifier is applied. Geometrical transformation is not applied to the alternative band classifier. When the band-based classifier is applied, the sum of sample values of a 2x2 luma block is calculated at first. Then the class index is calculated as below,
class_index = (sum *25) >> (sample bit depth + 2) .
In the present invention, methods and apparatus to improve the performance of ALF processing by using adaptive parameters for ALF classifier are disclosed.
BRIEF SUMMARY OF THE INVENTION
A method and apparatus for video coding using ALF (Adaptive Loop Filter) are disclosed. According to this method, reconstructed pixels are received, wherein the reconstructed pixels comprise a current block. One or more parameters for an ALF classifier are determined according to coding information associated with the current block or one or more statistical values of samples in a region. The ALF classifier, with a parameter set including said one or more parameters derived, is applied to target data associated with the current block to determine an ALF index. A target ALF is selected from an ALF set according to the ALF index. The target ALF is applied to the current block to generate filtered-reconstructed current block. The filtered-reconstructed current block is provided.
In one embodiment, said applying the ALF classifier comprises summing the target data within a window size (W) to obtain a sample sum, scaling the sample sum by a scaling factor (α) to determine a scaled sample sum, and right-shifting the scaled sample sum by a shifting factor (β) to determine a band index.
In one embodiment, the coding information comprises a slice type. For example, a β value used for intra slices is larger than that used for non-intra slices. In another example, an α value used for intra slices is smaller than that used for non-intra slices. In yet another example, the window size for intra slices is smaller than that for non-intra slices.
In one embodiment, the coding information comprises a QP (Quantization Parameter) at a slice level or a CU level. In one example, a β value used for low QP slices is larger than that used for high QP slices. In another example, an α value used for low QP slices is smaller than that used for high QP slices. In another example, the window size for low QP slices is smaller than that for high QP slices.
In one embodiment, said one or more statistical values of samples in the region correspond to a mean value of samples in a CTB. Furthermore, a look-up table is used to determine (α , β) based on the mean value of samples in the CTB. In another embodiment, said one or more statistical values of samples in the region correspond a minimum value and a maximum value of a sum of samples in a CTB. Furthermore, a look-up table is used to determine (α , β) based on the minimum value and the maximum value of the sum of samples in the CTB.
In one embodiment, the coding information comprises a slice type or a QP (Quantization Parameter) at a slice level or a CU level.
In one embodiment, the target data correspond to pre-ALF sample values.
In one embodiment, the target data correspond to absolute residual sample values.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1A illustrates an exemplary adaptive Inter/Intra video coding system incorporating loop processing.
Fig. 1B illustrates a corresponding decoder for the encoder in Fig. 1A.
Fig. 2 illustrates the ALF filter shapes for the chroma (left) and luma (right) components.
Figs. 3A-D illustrates the subsampled Laplacian calculations for g_v (3A) , g_h (3B) , g_d1 (3C) and g_d2 (3D) .
Fig. 4A illustrates the placement of CC-ALF with respect to other loop filters.
Fig. 4B illustrates a diamond shaped filter for the chroma samples.
Fig. 5 illustrates a flowchart of an exemplary video coding system that uses adaptive parameters for ALF classifier according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

It will be readily understood that the components of the present invention, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following more detailed description of the embodiments of the systems and methods of the present invention, as represented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. References throughout this specification to “one embodiment, ” “an embodiment, ” or similar language mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. Thus, appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. One skilled in the relevant art will recognize, however, that the invention can be practiced without one or more of the specific details, or with other methods, components, etc. In other instances, well-known structures, or operations are not shown or described in detail to avoid obscuring aspects of the invention. The illustrated embodiments of the invention will be best understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of apparatus and methods that are consistent with the invention as claimed herein.
Adaptive Parameters for ALF Classification
Different ALF classifiers provide different grouping results of blocks in a frame, and different grouping results lead to different optimized sum-of-square distortion (SSD) values. In ECM ALF, a filter set can select either a VVC-like gradient-based classifier or a band classifier. In JVET-AC0173 (Ikram Jumakulyyev, et al., “Non-EE2: ALF classification based on residual data” , Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29, 29th Meeting, by teleconference, 11–20 January 2023, Document: JVET-AC0173) , a new residual classifier is introduced, where the class is derived based on the sum of neighbouring absolute residual sample values. In the current design, the parameters of classifiers are fixed. However, it will be beneficial if the parameters could be adaptively changed according to the contents and/or the coding information, since the distribution of the samples may be very different. In this proposal, several methods related to such idea are illustrated.
In general, the classification rule of a band classifier can be written as

classIndex=f_m (bandIndex) ,
where s_i is the sample value at position i, W is a set of positions in a window, α and β are positive integers, f_m is a mapping function, and classIndex is the final classification result.
Based on such notation, the already-proposed classifiers are summarized in Table 3.
Table 3. Band Classifier and Residual Classifier
Note that the sample value in the notation can be from any available source, which is not limited to pre-ALF or residual sample values. The sample value (s_i) is also referred as target data in this disclosure.
We propose several methods related to adaptive parameters of a classifier in the following sections, where “parameters of a classifier” refer to W, α, β, and the parameters used in f_m. According to the present invention, one or more parameters of a classifier is derived adaptively.
In one embodiment, the parameters of a classifier are adaptively changed according to the slice type.
For example, in residual classifier, since intra slices tend to have larger absolute residual values, the parameters may be adaptively changed in the following ways:
1. The β value used for intra slices is larger than that used for non-intra slices.
2. The α value used for intra slices is smaller than that used for non-intra slices.
3. The window size of W for intra slices is smaller than that for non-intra slices.
In another embodiment, the parameters of a classifier are adaptively changed according to a QP value, where the QP can be slice-level QP or CU-level QP.
For example, in residual classifier, since slices with low QP tend to have larger absolute residual values, the parameters may be adaptively changed in the following ways:
1. The β value used for low QP slices is larger than that used for high QP slices.
2. The α value used for low QP slices is smaller than that used for high QP slices.
3. The window size of W for low QP slices is smaller than that for high QP slices.
In another embodiment, one or more statistical values of sample values in a region is calculated first, and the parameters of a classifier are adaptively changed according to the one or more statistical values.
For example, a mean value of sample values in a CTB is calculated, and a look-up table is used to determine the parameters (α, β) given the mean value.
For another example, sample sum of each window in a CTB is calculated first, and the minimum and the maximum of the sample sums are derived. A look-up table is used to determine the parameters (α, β) given the derived minimum and maximum values.
The above embodiments can be combined. That is, parameters of a classifier are adaptively changed according to more than one factor from the above embodiments.
For example, the parameters of a classifier are adaptively changed according to both slice type and QP value, where the QP can be slice-level QP or CU-level QP.
The foregoing proposed methods of adaptive parameters for ALF classifiers can be implemented in encoders and/or decoders. For example, any of the proposed methods can be implemented in the in-loop filter module (e.g. ILPF 130 in Fig. 1A and Fig. 1B) of an encoder or a decoder. Alternatively, any of the proposed methods can be implemented as a circuit coupled to reconstructed samples of an encoder or decoder. The ALF methods may also be implemented using executable software or firmware codes stored on a media, such as hard disk or flash memory, for a CPU (Central Processing Unit) or programmable devices (e.g. DSP (Digital Signal Processor) or FPGA (Field Programmable Gate Array) ) .
Fig. 5 illustrates a flowchart of an exemplary video coding system that uses adaptive parameters for ALF classifier according to an embodiment of the present invention. The steps shown in the flowchart may be implemented as program codes executable on one or more processors (e.g., one or more CPUs) at the encoder side. The steps shown in the flowchart may also be implemented based hardware such as one or more electronic devices or processors arranged to perform the steps in the flowchart. According to the method, reconstructed pixels are received in step 510, wherein the reconstructed pixels comprise a current block. One or more parameters for an ALF classifier are determined according to coding information associated with the current block or one or more statistical values of samples in a region in step 520. The ALF classifier, with a parameter set including said one or more parameters derived, is applied to target data associated with the current block to determine an ALF index in step 530. A target ALF is selected from an ALF set according to the ALF index in step 540. The target ALF is applied to the current block to generate filtered-reconstructed current block in step 550. The filtered-reconstructed current block is provided in step 560.
The flowchart shown is intended to illustrate an example of video coding according to the present invention. A person skilled in the art may modify each step, re-arranges the steps, split a step, or combine steps to practice the present invention without departing from the spirit of the present invention. In the disclosure, specific syntax and semantics have been used to illustrate examples to implement embodiments of the present invention. A skilled person may practice the present invention by substituting the syntax and semantics with equivalent syntax and semantics without departing from the spirit of the present invention.
The above description is presented to enable a person of ordinary skill in the art to practice the present invention as provided in the context of a particular application and its requirement. Various modifications to the described embodiments will be apparent to those with skill in the art, and the general principles defined herein may be applied to other embodiments. Therefore, the present invention is not intended to be limited to the particular embodiments shown and described, but is to be accorded the widest scope consistent with the principles and novel features herein disclosed. In the above detailed description, various specific details are illustrated in order to provide a thorough understanding of the present invention. Nevertheless, it will be understood by those skilled in the art that the present invention may be practiced.
Embodiment of the present invention as described above may be implemented in various hardware, software codes, or a combination of both. For example, an embodiment of the present invention can be one or more circuit circuits integrated into a video compression chip or program code integrated into video compression software to perform the processing described herein. An embodiment of the present invention may also be program code to be executed on a Digital Signal Processor (DSP) to perform the processing described herein. The invention may also involve a number of functions to be performed by a computer processor, a digital signal processor, a microprocessor, or field programmable gate array (FPGA) . These processors can be configured to perform particular tasks according to the invention, by executing machine-readable software code or firmware code that defines the particular methods embodied by the invention. The software code or firmware code may be developed in different programming languages and different formats or styles. The software code may also be compiled for different target platforms. However, different code formats, styles and languages of software codes and other means of configuring code to perform the tasks in accordance with the invention will not depart from the spirit and scope of the invention.
The invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described examples are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims

A method for Adaptive Loop Filter (ALF) processing of reconstructed video, the method comprising:

receiving reconstructed pixels, wherein the reconstructed pixels comprise a current block;

determining one or more parameters for an ALF classifier according to coding information associated with the current block or one or more statistical values of samples in a region;

applying the ALF classifier, with a parameter set including said one or more parameters derived, to target data associated with the current block to determine an ALF index;

selecting a target ALF from an ALF set according to the ALF index;

applying the target ALF to the current block to generate filtered-reconstructed current block; and

providing the filtered-reconstructed current block.
The method of Claim 1, wherein said applying the ALF classifier comprises summing the target data within a window size (W) to obtain a sample sum, scaling the sample sum by a scaling factor (α) to determine a scaled sample sum, and right-shifting the scaled sample sum by a shifting factor (β) to determine a band index.
The method of Claim 2, wherein the coding information comprises a slice type.
The method of Claim 3, wherein a β value used for intra slices is larger than that used for non-intra slices.
The method of Claim 3, wherein an α value used for intra slices is smaller than that used for non-intra slices.
The method of Claim 3, wherein the window size for intra slices is smaller than that for non-intra slices.
The method of Claim 2, wherein the coding information comprises a QP (Quantization Parameter) at a slice level or a CU level.
The method of Claim 7, wherein a β value used for low QP slices is larger than that used for high QP slices.
The method of Claim 7, wherein an α value used for low QP slices is smaller than that used for high QP slices.
The method of Claim 7, wherein the window size for low QP slices is smaller than that for high QP slices.
The method of Claim 2, wherein said one or more statistical values of samples in the region correspond to a mean value of samples in a CTB.
The method of Claim 11, wherein a look-up table is used to determine (α , β) based on the mean value of samples in the CTB.
The method of Claim 2, wherein said one or more statistical values of samples in the region correspond a minimum value and a maximum value of a sum of samples in a CTB.
The method of Claim 13, wherein a look-up table is used to determine (α , β) based on the minimum value and the maximum value of the sum of samples in the CTB.
The method of Claim 1, wherein the coding information comprises a slice type or a QP (Quantization Parameter) at a slice level or a CU level.
The method of Claim 1, wherein the target data correspond to pre-ALF sample values.
The method of Claim 1, wherein the target data correspond to absolute residual sample values.
An apparatus for video coding, the apparatus comprising one or more electronics or processors arranged to:

receive reconstructed pixels, wherein the reconstructed pixels comprise a current block;

determine one or more parameters for an ALF classifier according to coding information associated with the current block or one or more statistical values of samples in a region;

apply the ALF classifier, with a parameter set including said one or more parameters derived, to target data associated with the current block to determine an ALF index;

select a target ALF from an ALF set according to the ALF index;

apply the target ALF to the current block to generate filtered-reconstructed current block; and

provide the filtered-reconstructed current block.