Coding mode dependent adaptive filtering

Abstract

Methods and apparatus are provided for classification based adaptive filtering. At least one embodiment comprises selecting specific filters and filter sets depending on various classification criteria, including coding or prediction modes. The filtering is performed on reconstructed video in a video encoding or decoding process. In at least one of the embodiments, information is signaled from an encoder to a decoder that is indicative of a filter within a classification that is to be used.

Description

[0001]CODING MODE DEPENDENT ADAPTIVE FILTERING CROSS REFERENCE TO RELATED APPLICATION This application claims the benefit of European Serial No.23306534.1 filed September 18, 2023, which is incorporated by reference herein in its entirety. TECHNICAL FIELD At least one of the present embodiments generally relates to a method or an apparatus for video encoding or decoding, compression or decompression. BACKGROUND To achieve high compression efficiency, image and video coding schemes usually employ prediction, including motion vector prediction, and transform to leverage spatial and temporal redundancy in the video content. Generally, intra or inter prediction is used to exploit the intra or inter frame correlation, then the differences between the original image and the predicted image, often denoted as prediction errors or prediction residuals, are transformed, quantized, and entropy coded. To reconstruct the video, the compressed data are decoded by inverse processes corresponding to the entropy coding, quantization, transform, and prediction. SUMMARY At least one of the present embodiments generally relates to a method or an apparatus for video encoding or decoding, and more particularly, to a method or an apparatus for adaptive filtering in encoding or decoding video data. According to a first aspect, there is provided a method. The method comprises steps for filtering a portion of a digital video image based on a classification indicative of filter parameters; and encoding said digital video image using the filtered portion of said digital video image. According to a second aspect, there is provided another method. The method comprises steps for decoding a portion of a digital video image; and filtering said portion of said digital video image based on information indicative of filter parameters. According to another aspect, there is provided an apparatus. The apparatus comprises a processor. The processor can be configured to operate on digital video data according to the aforementioned methods. According to another aspect, there is provided an apparatus. The apparatus comprises a processor. The processor can be configured to encode a block of a video or decode video data by executing any of the aforementioned methods. According to another general aspect of at least one embodiment, there is provided a device comprising an apparatus according to any of the decoding embodiments; and at least one of (i) an antenna configured to receive a signal, the signal including the video block, (ii) a band limiter configured to limit the received signal to a band of frequencies that includes the video block, or (iii) a display configured to display an output representative of a video block. According to another general aspect of at least one embodiment, there is provided a non-transitory computer readable medium containing data content generated according to any of the described encoding embodiments or variants. According to another general aspect of at least one embodiment, there is provided a signal comprising video data generated according to any of the described encoding embodiments or variants. According to another general aspect of at least one embodiment, video data or a bitstream is formatted to include data content generated according to any of the described encoding embodiments or variants. According to another general aspect of at least one embodiment, there is provided a computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out any of the described decoding embodiments or variants. These and other aspects, features and advantages of the general aspects will become apparent from the following detailed description of exemplary embodiments, which is to be read in connection with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 illustrates an example of loop filters in VVC. Figure 2 illustrates an example (a) luma ALF 7x7 diamond-shape filter and (b) a chroma ALF 5X5 diamond-shape filter. Figure 3 illustrates an example of a signaled ALF filter set containing more than one filter in VVC. Figure 4 illustrates an example of a pre-trained ALF filter set in VVC. Figure 5 illustrates an example of a generic pre-trained filter set. Figure 6 illustrates an example of coding mode dependent adaptive filtering with separate banks of pre-trained filters. Figure 7 illustrates an example of coding mode dependent adaptive filtering with shared pre-trained filters. Figure 8 illustrates one embodiment of a first method under the described aspects. Figure 9 illustrates one embodiment of a second method under the described aspects Figure 10 illustrates one embodiment of an apparatus under the described aspects. Figure 11 illustrates a standard, generic, video compression scheme. Figure 12 illustrates a standard, generic, video decompression scheme. Figure 13 illustrates a processor-based system for encoding / decoding under the general described aspects. DETAILED DESCRIPTION The embodiments described here are in the field of video compression and generally relate to video compression and video encoding and decoding more specifically to adaptive filtering processes such as post-filters and in-loop filters, e.g. Adaptive-Loop Filters (ALF) or any other Wiener-based or linear convolution based post-filters. To achieve high compression efficiency, image and video coding schemes usually employ block-based prediction, including motion vector prediction, and transform to leverage spatial and temporal redundancy in the video content. Generally, intra or inter prediction is used to exploit the intra or inter frame correlation, then the differences between the original block and the predicted block, often denoted as prediction errors or prediction residuals, are transformed, quantized, and entropy coded. To reconstruct the video, the compressed data are decoded by inverse processes corresponding to the entropy coding, quantization, transform, and prediction. In the HEVC (High Efficiency Video Coding) video compression standard, motion compensated temporal prediction is employed to exploit the redundancy that exists between successive pictures of a video. To accomplish this, a motion vector is associated with each prediction unit (PU). Each CTU (Coding Tree Unit) is represented by a Coding Tree in the compressed domain. This is a quad-tree division of the CTU, where each leaf is called a Coding Unit (CU). Each CU is then given some Intra or Inter prediction parameters (Prediction Info). To do so, it is spatially partitioned into one or more Prediction Units (PUs), each PU being assigned some prediction information. The Intra or Inter coding mode is assigned on the CU level. Block-based intra / inter prediction and transform coding, together with quantization, induce a variety of artifacts at medium and low bitrates. In order to reduce those artifacts, video coding standards, such as VVC, and video coding solutions, such as ECM, implement in-loop filters, such as deblocking filtering (DBF), Bilateral filtering (BIF), Sample-adaptive offset (SAO) and Adaptive loop filtering (ALF). The parameters of adaptive filters, such as SAO and ALF, are determined at encoder-side by optimizing a rate-distortion criterion. Those filters parameters are transmitted along with the bitstream, then decoded and used at decoder side. A significant part of the gains provided by ALF on Luma is due to a further local adaptation achieved by classification: samples sharing the same local features are filtered with the same specific filter. Other kinds of classification have been proposed: e.g., based on color or component bands, based on residue energy, based on the variance of the reconstructed samples. This described embodiments address the problem of classifying samples in the most generic way, so that the filter optimization be as efficient as possible. The related art is recapped in the following. ADAPTIVE LOOP FILTER (ALF) Loop filters in Versatile Video Coding (VVC) The VVC standard implements three kinds of in-loop filters: deblocking filter (DBF), Sample-adaptive offset (SAO), and Adaptive loop filter (ALF). The deblocking filter aims at reducing blocking discontinuities. Sample-adaptive offset mostly aims at reducing artifacts resulting from the quantization of transform coefficients. Adaptive loop filter and Cross-component adaptive loop filter are adaptive filters enabling to enhance the reconstructed signal, using for instance Wiener-filter encoding approaches. The workflow of VVC in-loop filters is depicted in Figure 1. If local deblocking conditions are met, Luma and Chroma reconstructed samples located along block boundaries are first filtered with deblocking filters (DBF). Then offsets are added locally depending on a classification based on band-classifier or edge-classifier with Sample-adaptive offset (SAO). Eventually, Adaptive-loop filters (ALF) and Cross- component Adaptive loop filters (CCALF) are run before storing the resulting sample values in the Reference Picture buffer. ALF is an adaptive filter that is applied to reduce the MSE between the original and the reconstructed samples, using for instance Wiener-filter encoding approaches. ALF filters are transmitted in the bitstream and decoded at decoder side, derived from (previously) signaled parameters or derived from pre-defined parameters, before being applied on reconstructed samples. Cross-component Adaptive loop filter (CCALF) uses the Luma samples to refine Chroma sample values within the ALF process. ALF in VVC In VVC, ALF filters are point-symmetrical, DC-neutral with integer coefficients. ALF in VVC uses 7x7 diamond-shaped filters for Luma and 5x5 diamond-shaped filters Chroma, as depicted in Figure 2. Filtering operations Let ^^^ ^^, ^^^ be a reconstructed sample and let ^ത^^ ^^, ^^^ denote its ALF-filtered value. In the linear implementation of ALF, ^ത^^ ^^, ^^^ is computed as: ேିଶ^ത^^ ^^, ^^^ ൌ ^^^ ^^, ^^^ ^^^^^^ൈ ^∆ ^^^ା ^ ∆ ^^^^൩(1)Where ^ And: ∆ ^^^ାൌ ^^^ ^^ ^ ^^^, ^^ ^ ^^^^ െ ^^^ ^^, ^^^ ∆ൌ ^^^ ^^ െ ^^^ ^^ െ ^^^^ െ ^^^ ^^^(2)With ^േ ^^^,േ the reconstructed samples associated with the ^^-th coefficient ^^^In the non-linear implementation of ALF, Equation (1) becomes: ேିଶ^ത^^^^, ^^^ൌ ^^^^^, ^^^^ ^^ ^^^ ൈ^^^^ା^ ^^^ି^൩With: ^^^ା ൌ min൫^^^, max൫െ ^^^, ^^^ ^^ ^ ^^^, ^^ ^ ^^^^ െ ^^^ ^^, ^^^൯൯^^ିൌ min ^^ , max െ ^^ , ^^^ ^^ െ ^^ , ^^ െ ^ ^ ^ ^(4)^൫ ^ ൫ ^ ^ ^^ െ ^^ ^^, ^^ ൯൯Where ^^^is the clipping parameter associated with the coefficient ^^^, is determined a clipping index ^^^. The clipping parameter ^^^is derived as follows: ^^^ൌ ^ 2^^ when ^^^ ൌ 0otherwise(5)Where ^^ ^^ bit depth, and ^^ can be 0, 1, 2 or 3. ^Classification and filter set Classification is performed at a 4 ൈ 4 sub-block level on Luma, based on its directionality and Laplacian activity. Let D and A denote the directionality and the Laplacian activity, respectively, both derived from the computation of local horizontal, vertical, and diagonal gradients. The directionality D can take values in the range of 0 to 4, inclusively, as shown in Table 1. Directionality Value Texture 0 Weak horizontal / vertical 1 Strong horizontal / vertical 2 Weak diagonal 3 Strong diagonal 4 Table 1: Directionality for ALF classification in VVC. The activity A is derived from a local accumulation of the absolute values of local Laplacians, and can take values in the range of 0 to 4, inclusively. This leads to a 25-class classification. The class index is derived as follows: ^^ ൌ 5 ^^ ^ ^^ (6) Each class has a specific filter assigned to. A filter set contains up to 25 filters, together with a 25-index list if there is more than one filter. That list maps (look-up table) which filter shall be used for each class. An example of signalled filter set containing more than one filter is depicted in Figure 3. Online filter optimization and offline pre-training ALF filter coefficients and clipping indices are determined at encoder side, for instance by solving Wiener-Hopf equations to minimize the MSE between reconstructed samples and their original values. If a rate-distortion condition is met, these coefficients and, if applicable, the corresponding clipping indices, are encoded in an Adaptation Parameter Set (APS). In VVC, an ALF APS contains one Luma filter set and up to 8 Chroma filters. VVC also allows the uses of pre-trained (pre-defined) Luma filters and filter sets that are hard-coded both at encoder and decoder side. In VVC, there are 16 pre- trained filters sets together and 64 pre-trained filters. Figure 4 provides a schematic example of such a pre-trained filter set. Further developments in ECM ALF in Enhanced Compression Model (ECM) software presents further developments, which principal features related to classification are recapped below. Luma fixed filtering and related classification In ECM, "fixed" indicates that the filters are not derived online from picture samples, but that they were pre-trained offline. Fixed filters are therefore not signaled in the bistream; they are hard-coded both in encoder and decoder. To filter a Luma sample, three different classifiers ( ^^^, ^^^and ^^ଶand three different sets of filters (F0, F1 and F2) are used. Sets F0 and F1 contain fixed filters, with coefficients pre-trained for classifiers ^^^and ^^^. Coefficients of filters in F2 are signalled. Which filter from a set Fi is used for a given sample is decided by a class Ci assigned to this sample using classifier ^^^. The two classifiers corresponding to fixed filtering, ^^^and ^^^, are both Laplacian-based and applied on 2x2 sub-blocks. In both classifiers, activity and directionality values are derived based on vertical, horizontal, and diagonal gradients. Then a class index is determined based on the activity and directionality values. In ECM-2 to 9, the number of classes is 896 in both classifiers. Eight banks of QP-adapted filters are pre-trained for each classifier. Each QP-adapted bank contains 512 filters. Seven QP ranges are defined, and for each QP range, there are 2 filter set candidates for each classifier). Alternative 2x2 ALF classifier for Luma Luma classification is extended with an additional alternative classifier (named band classifier) for signalled filtering. Signalled Luma filter sets contain a flag that indicates 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) (7) ALF signalled filter classification based on residual data In addition to the Laplacian classifier and to the band-based classifier, one proposal is a new classifier that applies to the residual samples. The sum of absolute values of residual samples in a neighboring window is calculated, and the class index is derived as: classIdx = sum >> (sample bit depth - 2) (8) The value of classIdx is in the range of 0 to 24, like the previous two classifiers. Extended ALF fixed filter classification with variance In a JVET update, the classifiers of the fixed filters are extended. Firstly, for each 2x2 block, the mean value of a surrounding window is calculated. Then, for each sample of this window, the difference between the sample value and the mean value is calculated. A scaling factor is determined based on the activity value derived from a Laplacian classifier. The variance, i.e., the square root of the sum of the squared differences is further quantized to ^^ᇱby a scaling factor. The value of ^^′ is an integer between 0 and 7, inclusively. With ^^ ∈ ^0,1^, let ^^^denote the classifier from the classifier of ^^-th fixed filter in ECM-8.0. Then the proposed class index ^^^ᇱis derived as ^^^ᇱൌ ^^ᇱൈ 896 ^ ^^^(9) Variance-based classification for in-loop filters A variance-based classification for in-loop filtering has been proposed, namely for Bilateral filtering (BIF) and Adaptive loop filtering (ALF). For BIF, the variance of a TU is utilized to identify the texture strength. More filter strengths are introduced into BF. The filtering strength is determined by the variance. For ALF, each classification unit is classified into 2 levels of texture strength based on variance and boundary position jointly. Then the texture strength levels are further combined with the existing classifiers to output the final classification results. The described embodiments comprise using adaptive filters and filter sets that depend on the coding mode. The coding mode considered can refer to the slice / picture, or to the Coding Unit (CU). Depending on the coding mode, different adaptive filters and filter sets are used. The described embodiments comprise selecting specific filters and filter sets depending on coding or prediction modes. Classification-based adaptive filtering is considered here. Let K denote the number of classes in the classification. Consistent with the prior art, an adaptive filter set maps up to K filters on K classes, e.g. with a K-index list if there is more than one filter. That list specifies which filter shall be used for each class. Offline pre-trained filters and filter sets In an embodiment, pre-trained filters (i.e., filters that are not signaled in the bistream) and pre-trained filters sets (i.e., filter sets that not signaled in the bitstream either) are considered. A pre-trained filter set comprises a list of K indices that specifies a filter index for each class, together with potential additional information, that can e.g. specify the classifier that shall be used. Let N be the number of filters that were pre-trained offline and are hard-coded both in encoder and decoder. Figure 5 provides a schematic example of a generic pre- trained filter set. Let P be the number of filter sets that were pre-determined offline and also hard- coded both in encoder and decoder. At encoding time, the encoder selects according to a rate-distortion criterion which filter set shall be used accordingly with the coding mode, e.g. at CTU level, and signals the corresponding filter set index or indices in the bit-stream. At decoder side, the filter set indices are decoded, and the decoder selects, accordingly with the coding mode, the appropriate adaptive filter to be used. Determination of the coding mode Slice / picture coding mode In a variant, the coding mode considered refers to the current slice or picture. Depending on whether the current slice is inter- or intra-coded, the filter set index used is selected among the P filter sets dedicated to inter or intra sample, respectively. Coding Unit (CU) prediction mode In another variant, the coding mode considered refers to the prediction mode of the Coding Unit (CU) the current sample belongs to. Two prediction modes are considered, namely intra prediction and inter prediction. Intra Block Copy (IBC) and Combined Inter / Intra Block Prediction (CIIP) can be considered either as an intra prediction mode, or as an inter prediction mode. In that variant, both inter and intra filter set indices are signalled, e.g. at CTU level. Coding mode dependent pre-trained filter sets In ECM-2 to 9, where such coding mode dependency is not implemented, there are two fixed filtering classifiers and eight banks of QP-adapted pre-trained filters per classifier. For both classifiers, K equals to 896. Each QP-adapted bank contains N=512 filters. Seven QP ranges are defined, and for each QP range, P equals to 2 (two filter set candidates per QP range for each classifier). Separate inter / intra filter banks In an embodiment, the pre-trained filter banks for inter and for intra-samples are pre-trained independently and therefore comprise two separate filter banks, as illustrated in Figure 6. That is: there are two LUTs, one for intra samples and the other for inter samples, and there are two pre-trained filter banks, one for intra samples and the other for inter samples. In that embodiment, the definition of coding mode dependent pre-trained filters and filter sets can be illustrated with the following pseudo-code: classToFilterIdx[NB_CODING_MODE][NB_QP][NB_CLASSIFIER][NB_CLASS] = { / / LUT intra { { / *QP1* / { / *classifier1* / <array of K indices> }, { / *classifier2* / [...] } }, { [...] } }, } }, inter { / *classifier1* / <array of K indices> }, { / *classifier2* / […] } }, { […] } }, } } [NB_CODING_MODE][NB_QP][NB_CLASSIFIER][NB_FILTER][NB_COEF] { / / Intra filter bank { { / *QP1* / { / *classifier1* / <N filters of NB_COEFF each> }, { / *classifier2* / [...] } }, { / *QP2* / [...] }, { [...] } }, / / Inter filter bank { { / *QP1* / { / *classifier1* / <N filters of NB_COEFF each> }, { / *classifier2* / [...] } }, { / *QP2* / [...] }, { [...] } } }; Where “ / / …” and “ / * … * / ” denote informative comments, classToFilterIdx denotes the pre-trained filter sets, filterCoef denotes the array of pre-trained filter coefficients, NB_CODING_MODE denotes the number of coding modes considered, NB_QP denotes the number of QPs considered during offline filter training, NB_CLASSIFIER denotes the number of classifiers, NB_CLASS denotes the number of in the classifications (that is, using previous notations: K), NB_FILTER denotes the number of filters pre-trained per QP and per classifier (that is, using previous notations: N), and NB_COEF denotes the number of coefficients defined per filter. Shared pre-trained filter bank In another embodiment, both inter and intra pre-trained filter sets map, through look-up tables (LUTs), to the same bank of pre-trained filters, as illustrated in Figure 7. One LUT is defined for intra coding mode (used for samples coded intra), another LUT is defined for inter coding mode (used for samples coded inter). In that embodiment, the definition of coding mode dependent pre-trained filters and filter sets can be illustrated with the following pseudo-code: classToFilterIdx[NB_CODING_MODE][NB_QP][NB_CLASSIFIER][NB_CLASS] = { / / LUT intra { { / *QP1* / { / *classifier1* / <array of K indices> }, { / *classifier2* / [...] } }, { [...] } }, } }, inter { / *classifier1* / <array of K indices> }, { / *classifier2* / […] } }, { […] } }, } } [NB_QP][NB_CLASSIFIER][NB_FILTER][NB_COEF] = { / *classifier1* / <N_filters_of_size_NB_COEFF> }, { / *classifier2* / [...] } }, { / *QP2* / [...] }, { [...] } }; Where, just like in previous embodiment, “ / / …” and “ / * … * / ” denote informative comments, classToFilterIdx denotes the pre-trained filter sets, filterCoef denotes the array of pre-trained filter coefficients, NB_CODING_MODE denotes the number of coding modes considered, NB_QP denotes the number of QPs considered during offline filter training, NB_CLASSIFIER denotes the number of classifiers, NB_CLASS denotes the number of in the classifications (that is, using previous notations: K), NB_FILTER denotes the number of filters pre-trained per QP and per classifier (that is, using previous notations: N), and NB_COEF denotes the number of coefficients defined per filter. Signaled filters In another embodiment, filters that are derived online from video samples and signaled in the bistream are considered. Corresponding filter sets also are necessarily signaled in the bistream, and comprise up to K filters, together, if there are more than one, with a list of K indices that specifies which filter shall be used for each class, plus potential additional information, that can e.g. specify the classifier that shall be used. Coding mode dependent adaptive filter sets contain additional information, e.g. an index, that specifies the coding mode they relate to. At encoding time, the encoder computes one or several MSE-optimal filter sets for each coding mode, e.g., on a slice or picture basis, then determines according to a rate-distortion criterion whether to signal those filter sets or not. At decoder side, the signaled filter sets are decoded, then can be used accordingly with their specific coding mode in subsequent slices / pictures. One embodiment of a method 800 under the general aspects described here is shown in Figure 8. The method commences at start block 801 and control proceeds to block 810 for filtering a portion of a digital video image based on a classification indicative of filter parameters. Control proceeds from block 810 to block 820 for encoding said digital video image using the filtered portion of said digital video image. One embodiment of a method 900 under the general aspects described here is shown in Figure 9. The method commences at start block 901 and control proceeds to block 910 for decoding a portion of a digital video image. Control proceeds from block 910 to block 920 for filtering said portion of said digital video image based on information indicative of filter parameters. Figure 10 shows one embodiment of an apparatus 1300 for encoding, decoding, compressing or decompressing, or filtering of video data using the aforementioned methods. The apparatus comprises Processor 1310 and can be interconnected to a memory 1320 through at least one port. Both Processor 1310 and memory 1320 can also have one or more additional interconnections to external connections. Processor 1310 is also configured to either insert or receive information in a bitstream and, either compressing, encoding, or decoding using any of the described aspects. The embodiments described here include a variety of aspects, including tools, features, embodiments, models, approaches, etc. Many of these aspects are described with specificity and, at least to show the individual characteristics, are often described in a manner that may sound limiting. However, this is for purposes of clarity in description, and does not limit the application or scope of those aspects. Indeed, all of the different aspects can be combined and interchanged to provide further aspects. Moreover, the aspects can be combined and interchanged with aspects described in earlier filings as well. The aspects described and contemplated in this application can be implemented in many different forms. Figures 11, 12, and 13 provide some embodiments, but other embodiments are contemplated and the discussion of Figures 11, 12, and 13 does not limit the breadth of the implementations. At least one of the aspects generally relates to video encoding and decoding, and at least one other aspect generally relates to transmitting a bitstream generated or encoded. These and other aspects can be implemented as a method, an apparatus, a computer readable storage medium having stored thereon instructions for encoding or decoding video data according to any of the methods described, and / or a computer readable storage medium having stored thereon a bitstream generated according to any of the methods described. In the present application, the terms “reconstructed” and “decoded” may be used interchangeably, the terms “pixel” and “sample” may be used interchangeably, the terms “image,” “picture” and “frame” may be used interchangeably. Usually, but not necessarily, the term “reconstructed” is used at the encoder side while “decoded” is used at the decoder side. Various methods are described herein, and each of the methods comprises one or more steps or actions for achieving the described method. Unless a specific order of steps or actions is required for proper operation of the method, the order and / or use of specific steps and / or actions may be modified or combined. Various methods and other aspects described in this application can be used to modify modules, for example, the intra prediction, entropy coding, and / or decoding modules (160, 260, 145, 230), of a video encoder 100 and decoder 200 as shown in Figure 11 and Figure 12. Moreover, the present aspects are not limited to VVC or HEVC, and can be applied, for example, to other standards and recommendations, whether pre-existing or future-developed, and extensions of any such standards and recommendations (including VVC and HEVC). Unless indicated otherwise, or technically precluded, the aspects described in this application can be used individually or in combination. Various numeric values are used in the present application. The specific values are for example purposes and the aspects described are not limited to these specific values. Figure 11 illustrates an encoder 100. Variations of this encoder 100 are contemplated, but the encoder 100 is described below for purposes of clarity without describing all expected variations. Before being encoded, the video sequence may go through pre-encoding processing (101), for example, applying a color transform to the input color picture (e.g., conversion from RGB 4:4:4 to YCbCr 4:2:0), or performing a remapping of the input picture components in order to get a signal distribution more resilient to compression (for instance using a histogram equalization of one of the color components). Metadata can be associated with the pre-processing and attached to the bitstream. In the encoder 100, a picture is encoded by the encoder elements as described below. The picture to be encoded is partitioned (102) and processed in units of, for example, CUs. Each unit is encoded using, for example, either an intra or inter mode. When a unit is encoded in an intra mode, it performs intra prediction (160). In an inter mode, motion estimation (175) and compensation (170) are performed. The encoder decides (105) which one of the intra mode or inter mode to use for encoding the unit, and indicates the intra / inter decision by, for example, a prediction mode flag. Prediction residuals are calculated, for example, by subtracting (110) the predicted block from the original image block. The prediction residuals are then transformed (125) and quantized (130). The quantized transform coefficients, as well as motion vectors and other syntax elements, are entropy coded (145) to output a bitstream. The encoder can skip the transform and apply quantization directly to the non-transformed residual signal. The encoder can bypass both transform and quantization, i.e., the residual is coded directly without the application of the transform or quantization processes. The encoder decodes an encoded block to provide a reference for further predictions. The quantized transform coefficients are de-quantized (140) and inverse transformed (150) to decode prediction residuals. Combining (155) the decoded prediction residuals and the predicted block, an image block is reconstructed. In-loop filters (165) are applied to the reconstructed picture to perform, for example, deblocking / SAO (Sample Adaptive Offset) filtering to reduce encoding artifacts. The filtered image is stored at a reference picture buffer (180). Figure 12 illustrates a block diagram of a video decoder 200. In the decoder 200, a bitstream is decoded by the decoder elements as described below. Video decoder 200 generally performs a decoding pass reciprocal to the encoding pass as described in Figure 11. The encoder 100 also generally performs video decoding as part of encoding video data. In particular, the input of the decoder includes a video bitstream, which can be generated by video encoder 100. The bitstream is first entropy decoded (230) to obtain transform coefficients, motion vectors, and other coded information. The picture partition information indicates how the picture is partitioned. The decoder may therefore divide (235) the picture according to the decoded picture partitioning information. The transform coefficients are de-quantized (240) and inverse transformed (250) to decode the prediction residuals. Combining (255) the decoded prediction residuals and the predicted block, an image block is reconstructed. The predicted block can be obtained (270) from intra prediction (260) or motion- compensated prediction (i.e., inter prediction) (275). In-loop filters (265) are applied to the reconstructed image. The filtered image is stored at a reference picture buffer (280). The decoded picture can further go through post-decoding processing (285), for example, an inverse color transform (e.g. conversion from YcbCr 4:2:0 to RGB 4:4:4) or an inverse remapping performing the inverse of the remapping process performed in the pre-encoding processing (101). The post-decoding processing can use metadata derived in the pre-encoding processing and signaled in the bitstream. Figure 13 illustrates a block diagram of an example of a system in which various aspects and embodiments are implemented. System 1000 can be embodied as a device including the various components described below and is configured to perform one or more of the aspects described in this document. Examples of such devices include, but are not limited to, various electronic devices such as personal computers, laptop computers, smartphones, tablet computers, digital multimedia set top boxes, digital television receivers, personal video recording systems, connected home appliances, and servers. Elements of system 1000, singly or in combination, can be embodied in a single integrated circuit (IC), multiple ICs, and / or discrete components. For example, in at least one embodiment, the processing and encoder / decoder elements of system 1000 are distributed across multiple ICs and / or discrete components. In various embodiments, the system 1000 is communicatively coupled to one or more other systems, or other electronic devices, via, for example, a communications bus or through dedicated input and / or output ports. In various embodiments, the system 1000 is configured to implement one or more of the aspects described in this document. The system 1000 includes at least one processor 1010 configured to execute instructions loaded therein for implementing, for example, the various aspects described in this document. Processor 1010 can include embedded memory, input output interface, and various other circuitries as known in the art. The system 1000 includes at least one memory 1020 (e.g., a volatile memory device, and / or a non- volatile memory device). System 1000 includes a storage device 1040, which can include non-volatile memory and / or volatile memory, including, but not limited to, Electrically Erasable Programmable Read-Only Memory (EEPROM), Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), Random Access Memory (RAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), flash, magnetic disk drive, and / or optical disk drive. The storage device 1040 can include an internal storage device, an attached storage device (including detachable and non-detachable storage devices), and / or a network accessible storage device, as non-limiting examples. System 1000 includes an encoder / decoder module 1030 configured, for example, to process data to provide an encoded video or decoded video, and the encoder / decoder module 1030 can include its own processor and memory. The encoder / decoder module 1030 represents module(s) that can be included in a device to perform the encoding and / or decoding functions. As is known, a device can include one or both of the encoding and decoding modules. Additionally, encoder / decoder module 1030 can be implemented as a separate element of system 1000 or can be incorporated within processor 1010 as a combination of hardware and software as known to those skilled in the art. Program code to be loaded onto processor 1010 or encoder / decoder 1030 to perform the various aspects described in this document can be stored in storage device 1040 and subsequently loaded onto memory 1020 for execution by processor 1010. In accordance with various embodiments, one or more of processor 1010, memory 1020, storage device 1040, and encoder / decoder module 1030 can store one or more of various items during the performance of the processes described in this document. Such stored items can include, but are not limited to, the input video, the decoded video or portions of the decoded video, the bitstream, matrices, variables, and intermediate or final results from the processing of equations, formulas, operations, and operational logic. In some embodiments, memory inside of the processor 1010 and / or the encoder / decoder module 1030 is used to store instructions and to provide working memory for processing that is needed during encoding or decoding. In other embodiments, however, a memory external to the processing device (for example, the processing device can be either the processor 1010 or the encoder / decoder module 1030) is used for one or more of these functions. The external memory can be the memory 1020 and / or the storage device 1040, for example, a dynamic volatile memory and / or a non-volatile flash memory. In several embodiments, an external non-volatile flash memory is used to store the operating system of, for example, a television. In at least one embodiment, a fast external dynamic volatile memory such as a RAM is used as working memory for video coding and decoding operations, such as for MPEG-2 (MPEG refers to the Moving Picture Experts Group, MPEG-2 is also referred to as ISO / IEC 13818, and 13818-1 is also known as H.222, and 13818-2 is also known as H.262), HEVC (HEVC refers to High Efficiency Video Coding, also known as H.265 and MPEG-H Part 2), or VVC (Versatile Video Coding, a new standard being developed by JVET, the Joint Video Experts Team). The input to the elements of system 1000 can be provided through various input devices as indicated in block 1130. Such input devices include, but are not limited to, (i) a radio frequency (RF) portion that receives an RF signal transmitted, for example, over the air by a broadcaster, (ii) a Component (COMP) input terminal (or a set of COMP input terminals), (iii) a Universal Serial Bus (USB) input terminal, and / or (iv) a High Definition Multimedia Interface (HDMI) input terminal. Other examples, not shown in Figure 13, include composite video. In various embodiments, the input devices of block 1130 have associated respective input processing elements as known in the art. For example, the RF portion can be associated with elements suitable for (i) selecting a desired frequency (also referred to as selecting a signal, or band-limiting a signal to a band of frequencies), (ii) downconverting the selected signal, (iii) band-limiting again to a narrower band of frequencies to select (for example) a signal frequency band which can be referred to as a channel in certain embodiments, (iv) demodulating the downconverted and band- limited signal, (v) performing error correction, and (vi) demultiplexing to select the desired stream of data packets. The RF portion of various embodiments includes one or more elements to perform these functions, for example, frequency selectors, signal selectors, band-limiters, channel selectors, filters, downconverters, demodulators, error correctors, and demultiplexers. The RF portion can include a tuner that performs various of these functions, including, for example, downconverting the received signal to a lower frequency (for example, an intermediate frequency or a near-baseband frequency) or to baseband. In one set-top box embodiment, the RF portion and its associated input processing element receives an RF signal transmitted over a wired (for example, cable) medium, and performs frequency selection by filtering, downconverting, and filtering again to a desired frequency band. Various embodiments rearrange the order of the above-described (and other) elements, remove some of these elements, and / or add other elements performing similar or different functions. Adding elements can include inserting elements in between existing elements, such as, for example, inserting amplifiers and an analog-to-digital converter. In various embodiments, the RF portion includes an antenna. Additionally, the USB and / or HDMI terminals can include respective interface processors for connecting system 1000 to other electronic devices across USB and / or HDMI connections. It is to be understood that various aspects of input processing, for example, Reed-Solomon error correction, can be implemented, for example, within a separate input processing IC or within processor 1010 as necessary. Similarly, aspects of USB or HDMI interface processing can be implemented within separate interface Ics or within processor 1010 as necessary. The demodulated, error corrected, and demultiplexed stream is provided to various processing elements, including, for example, processor 1010, and encoder / decoder 1030 operating in combination with the memory and storage elements to process the datastream as necessary for presentation on an output device. Various elements of system 1000 can be provided within an integrated housing, Within the integrated housing, the various elements can be interconnected and transmit data therebetween using suitable connection arrangement, for example, an internal bus as known in the art, including the Inter-IC (I2C) bus, wiring, and printed circuit boards. The system 1000 includes communication interface 1050 that enables communication with other devices via communication channel 1060. The communication interface 1050 can include, but is not limited to, a transceiver configured to transmit and to receive data over communication channel 1060. The communication interface 1050 can include, but is not limited to, a modem or network card and the communication channel 1060 can be implemented, for example, within a wired and / or a wireless medium. Data is streamed, or otherwise provided, to the system 1000, in various embodiments, using a wireless network such as a Wi-Fi network, for example IEEE 802.11 (IEEE refers to the Institute of Electrical and Electronics Engineers). The Wi- Fi signal of these embodiments is received over the communications channel 1060 and the communications interface 1050 which are adapted for Wi-Fi communications. The communications channel 1060 of these embodiments is typically connected to an access point or router that provides access to external networks including the Internet for allowing streaming applications and other over-the-top communications. Other embodiments provide streamed data to the system 1000 using a set-top box that delivers the data over the HDMI connection of the input block 1130. Still other embodiments provide streamed data to the system 1000 using the RF connection of the input block 1130. As indicated above, various embodiments provide data in a non- streaming manner. Additionally, various embodiments use wireless networks other than Wi-Fi, for example a cellular network or a Bluetooth network. The system 1000 can provide an output signal to various output devices, including a display 1100, speakers 1110, and other peripheral devices 1120. The display 1100 of various embodiments includes one or more of, for example, a touchscreen display, an organic light-emitting diode (OLED) display, a curved display, and / or a foldable display. The display 1100 can be for a television, a tablet, a laptop, a cell phone (mobile phone), or another device. The display 1100 can also be integrated with other components (for example, as in a smart phone), or separate (for example, an external monitor for a laptop). The other peripheral devices 1120 include, in various examples of embodiments, one or more of a stand-alone digital video disc (or digital versatile disc) (DVR, for both terms), a disk player, a stereo system, and / or a lighting system. Various embodiments use one or more peripheral devices 1120 that provide a function based on the output of the system 1000. For example, a disk player performs the function of playing the output of the system 1000. In various embodiments, control signals are communicated between the system 1000 and the display 1100, speakers 1110, or other peripheral devices 1120 using signaling such as AV.Link, Consumer Electronics Control (CEC), or other communications protocols that enable device-to-device control with or without user intervention. The output devices can be communicatively coupled to system 1000 via dedicated connections through respective interfaces 1070, 1080, and 1090. Alternatively, the output devices can be connected to system 1000 using the communications channel 1060 via the communications interface 1050. The display 1100 and speakers 1110 can be integrated in a single unit with the other components of system 1000 in an electronic device such as, for example, a television. In various embodiments, the display interface 1070 includes a display driver, such as, for example, a timing controller (T Con) chip. The display 1100 and speaker 1110 can alternatively be separate from one or more of the other components, for example, if the RF portion of input 1130 is part of a separate set-top box. In various embodiments in which the display 1100 and speakers 1110 are external components, the output signal can be provided via dedicated output connections, including, for example, HDMI ports, USB ports, or COMP outputs. The embodiments can be carried out by computer software implemented by the processor 1010 or by hardware, or by a combination of hardware and software. As a non-limiting example, the embodiments can be implemented by one or more integrated circuits. The memory 1020 can be of any type appropriate to the technical environment and can be implemented using any appropriate data storage technology, such as optical memory devices, magnetic memory devices, semiconductor-based memory devices, fixed memory, and removable memory, as non-limiting examples. The processor 1010 can be of any type appropriate to the technical environment, and can encompass one or more of microprocessors, general purpose computers, special purpose computers, and processors based on a multi-core architecture, as non- limiting examples. Various implementations involve decoding. “Decoding”, as used in this application, can encompass all or part of the processes performed, for example, on a received encoded sequence to produce a final output suitable for display. In various embodiments, such processes include one or more of the processes typically performed by a decoder, for example, entropy decoding, inverse quantization, inverse transformation, and differential decoding. In various embodiments, such processes also, or alternatively, include processes performed by a decoder of various implementations described in this application. As further examples, in one embodiment “decoding” refers only to entropy decoding, in another embodiment “decoding” refers only to differential decoding, and in another embodiment “decoding” refers to a combination of entropy decoding and differential decoding. Whether the phrase “decoding process” is intended to refer specifically to a subset of operations or generally to the broader decoding process will be clear based on the context of the specific descriptions and is believed to be well understood by those skilled in the art. Various implementations involve encoding. In an analogous way to the above discussion about “decoding”, “encoding” as used in this application can encompass all or part of the processes performed, for example, on an input video sequence to produce an encoded bitstream. In various embodiments, such processes include one or more of the processes typically performed by an encoder, for example, partitioning, differential encoding, transformation, quantization, and entropy encoding. In various embodiments, such processes also, or alternatively, include processes performed by an encoder of various implementations described in this application. As further examples, in one embodiment “encoding” refers only to entropy encoding, in another embodiment “encoding” refers only to differential encoding, and in another embodiment “encoding” refers to a combination of differential encoding and entropy encoding. Whether the phrase “encoding process” is intended to refer specifically to a subset of operations or generally to the broader encoding process will be clear based on the context of the specific descriptions and is believed to be well understood by those skilled in the art. Note that the syntax elements as used herein are descriptive terms. As such, they do not preclude the use of other syntax element names. When a figure is presented as a flow diagram, it should be understood that it also provides a block diagram of a corresponding apparatus. Similarly, when a figure is presented as a block diagram, it should be understood that it also provides a flow diagram of a corresponding method / process. Various embodiments may refer to parametric models or rate distortion optimization. In particular, during the encoding process, the balance or trade-off between the rate and distortion is usually considered, often given the constraints of computational complexity. It can be measured through a Rate Distortion Optimization (RDO) metric, or through Least Mean Square (LMS), Mean of Absolute Errors (MAE), or other such measurements. Rate distortion optimization is usually formulated as minimizing a rate distortion function, which is a weighted sum of the rate and of the distortion. There are different approaches to solve the rate distortion optimization problem. For example, the approaches may be based on an extensive testing of all encoding options, including all considered modes or coding parameters values, with a complete evaluation of their coding cost and related distortion of the reconstructed signal after coding and decoding. Faster approaches may also be used, to save encoding complexity, in particular with computation of an approximated distortion based on the prediction or the prediction residual signal, not the reconstructed one. Mix of these two approaches can also be used, such as by using an approximated distortion for only some of the possible encoding options, and a complete distortion for other encoding options. Other approaches only evaluate a subset of the possible encoding options. More generally, many approaches employ any of a variety of techniques to perform the optimization, but the optimization is not necessarily a complete evaluation of both the coding cost and related distortion. The implementations and aspects described herein can be implemented in, for example, a method or a process, an apparatus, a software program, a data stream, or a signal. Even if only discussed in the context of a single form of implementation (for example, discussed only as a method), the implementation of features discussed can also be implemented in other forms (for example, an apparatus or program). An apparatus can be implemented in, for example, appropriate hardware, software, and firmware. The methods can be implemented in, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device. Processors also include communication devices, such as, for example, computers, cell phones, portable / personal digital assistants (“PDAs”), and other devices that facilitate communication of information between end-users. Reference to “one embodiment” or “an embodiment” or “one implementation” or “an implementation”, as well as other variations thereof, means that a particular feature, structure, characteristic, and so forth described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrase “in one embodiment” or “in an embodiment” or “in one implementation” or “in an implementation”, as well any other variations, appearing in various places throughout this application are not necessarily all referring to the same embodiment. Additionally, this application may refer to “determining” various pieces of information. Determining the information can include one or more of, for example, estimating the information, calculating the information, predicting the information, or retrieving the information from memory. Further, this application may refer to “accessing” various pieces of information. Accessing the information can include one or more of, for example, receiving the information, retrieving the information (for example, from memory), storing the information, moving the information, copying the information, calculating the information, determining the information, predicting the information, or estimating the information. Additionally, this application may refer to “receiving” various pieces of information. Receiving is, as with “accessing”, intended to be a broad term. Receiving the information can include one or more of, for example, accessing the information, or retrieving the information (for example, from memory). Further, “receiving” is typically involved, in one way or another, during operations such as, for example, storing the information, processing the information, transmitting the information, moving the information, copying the information, erasing the information, calculating the information, determining the information, predicting the information, or estimating the information. It is to be appreciated that the use of any of the following “ / ”, “and / or”, and “at least one of”, for example, in the cases of “A / B”, “A and / or B” and “at least one of A and B”, is intended to encompass the selection of the first listed option (A) only, or the selection of the second listed option (B) only, or the selection of both options (A and B). As a further example, in the cases of “A, B, and / or C” and “at least one of A, B, and C”, such phrasing is intended to encompass the selection of the first listed option (A) only, or the selection of the second listed option (B) only, or the selection of the third listed option (C) only, or the selection of the first and the second listed options (A and B) only, or the selection of the first and third listed options (A and C) only, or the selection of the second and third listed options (B and C) only, or the selection of all three options (A and B and C). This may be extended, as is clear to one of ordinary skill in this and related arts, for as many items as are listed. Also, as used herein, the word “signal” refers to, among other things, indicating something to a corresponding decoder. For example, in certain embodiments the encoder signals a particular one of a plurality of transforms, coding modes or flags. In this way, in an embodiment the same transform, parameter, or mode is used at both the encoder side and the decoder side. Thus, for example, an encoder can transmit (explicit signaling) a particular parameter to the decoder so that the decoder can use the same particular parameter. Conversely, if the decoder already has the particular parameter as well as others, then signaling can be used without transmitting (implicit signaling) to simply allow the decoder to know and select the particular parameter. By avoiding transmission of any actual functions, a bit savings is realized in various embodiments. It is to be appreciated that signaling can be accomplished in a variety of ways. For example, one or more syntax elements, flags, and so forth are used to signal information to a corresponding decoder in various embodiments. While the preceding relates to the verb form of the word “signal”, the word “signal” can also be used herein as a noun. As will be evident to one of ordinary skill in the art, implementations can produce a variety of signals formatted to carry information that can be, for example, stored or transmitted. The information can include, for example, instructions for performing a method, or data produced by one of the described implementations. For example, a signal can be formatted to carry the bitstream of a described embodiment. Such a signal can be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal. The formatting can include, for example, encoding a data stream and modulating a carrier with the encoded data stream. The information that the signal carries can be, for example, analog or digital information. The signal can be transmitted over a variety of different wired or wireless links, as is known. The signal can be stored on a processor-readable medium. The preceding sections describe a number of embodiments, across various claim categories and types. Features of these embodiments can be provided alone or in any combination. Further, embodiments can include one or more of the following features, devices, or aspects, alone or in any combination, across various claim categories and types: At least one embodiment comprises implementing a filtering operation adaptively by using one of a plurality of filters. At least one embodiment comprises encoding or decoding a video block by using filtering in a reconstructed video path according to the described embodiments. At least one embodiment comprises the above embodiment to implement an Adaptive Loop Filter. At least one embodiment further comprises classifications to be used in determining filter sets to use for in-loop filtering. At least one embodiment further comprises the above embodiments wherein an index is used to select a filter within a filter set. At least one embodiment further comprises the above embodiments wherein a classification is based on coding mode or prediction mode. At least one embodiment comprises the above embodiments wherein classification is based on directionality of a video image. At least one embodiment comprises any encoding or decoding operation based on the above operations. At least one embodiment comprises performing encoding or decoding with the aforementioned methods on a sub-block. At least one embodiment comprises a bitstream or signal that includes one or more of the described syntax elements, or variations thereof. At least one embodiment comprises a bitstream or signal that includes syntax conveying information generated according to any of the embodiments described. At least one embodiment comprises creating and / or transmitting and / or receiving and / or decoding according to any of the embodiments described. At least one embodiment comprises a method, process, apparatus, medium storing instructions, medium storing data, or signal according to any of the embodiments described. At least one embodiment comprises inserting in the signaling syntax elements that enable the decoder to determine decoding information in a manner corresponding to that used by an encoder. At least one embodiment comprises creating and / or transmitting and / or receiving and / or decoding a bitstream or signal that includes one or more of the described syntax elements, or variations thereof. At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that performs transform method(s) according to any of the embodiments described. At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that performs transform method(s) determination according to any of the embodiments described, and that displays (e.g., using a monitor, screen, or other type of display) a resulting image. At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that selects, bandlimits, or tunes (e.g., using a tuner) a channel to receive a signal including an encoded image, and performs transform method(s) according to any of the embodiments described. At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that receives (e.g., using an antenna) a signal over the air that includes an encoded image, and performs transform method(s).

Claims

CLAIMS 1. A method, comprising: filtering a portion of a digital video image based on a classification indicative of filter parameters; and encoding said digital video image using the filtered portion of said digital video image.

2. An apparatus, comprising: a memory, and a processor, configured to: filter a portion of a digital video image based on a classification indicative of filter parameters; and encode said digital video image using the filtered portion of said digital video image.

3. A method, comprising: decoding a portion of a digital video image; and filtering said portion of said digital video image based on information indicative of filter parameters.

4. An apparatus, comprising: a memory, and a processor, configured to: decode a portion of a digital video image; and filter said portion of said digital video image based on information indicative of filter parameters.

5. The method of Claim 1 or 3, or the apparatus of Claim 2 or 4, wherein said filtering is performed on an in-loop component in an encoding or decoding process.

6. The method of any one of Claims 1 or 5, or the apparatus of any one of Claims 2 or 5, wherein said classification is indicative of a set of filters.

7. The method of any one of Claims 1 or 5 or 6, or the apparatus of any one of Claims 2 or 5 or 6, wherein said classification is based on prediction mode.

8. The method of any one of Claims 1, 3, or 5-6, or the apparatus of any one of Claims 2, 4, or 5-6, wherein an index is used to indicate said filter parameters within a set.

9. The method of any one of Claims 1, 3, or 5 through 8, or the apparatus of any one of Claims 2, 4, or 5 through 8, wherein separate filter banks are used for intercoded and intracoded samples and are pre-trained independently.

10. The method of any one of Claims 1, 3, or 5 through 9, or the apparatus of any one of Claims 2, 4, or 5 through 9, wherein filter parameters are determined at a coding unit level.

11. The method of any one of Claims 1, 3, or 5 through 10, or the apparatus of any one of Claims 2, 4, or 5 through 10 wherein information indicative of a filter is signaled in a bitstream.

12. A device comprising: an apparatus according to Claim 2; and at least one of (i) an antenna configured to receive a signal, the signal including the video block, (ii) a band limiter configured to limit the received signal to a band of frequencies that includes the video block, and (iii) a display configured to display an output representative of a video block.

13. A non-transitory computer readable medium containing data content generated according to the method of any one of claims 1, or 3 through 11, or by the apparatus of any one of claims 2, or 3 through 11, for playback using a processor.

14. A signal comprising video data generated according to the method of any one of claims 1, or 3 through 11, or by the apparatus of any one of claims 2, or 3 through 11, for playback using a processor.

15. A computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method of any one of claims 1, or 3 through 11.

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