An apparatus, a method and a computer program for video coding and decoding

Abstract

A method comprising: obtaining a first set of reconstructed samples of a first color channel of an image; obtaining a second set of reconstructed samples of a second color channel of the image; applying a first adaptive in-loop filter for the first set of reconstructed samples; applying a second adaptive in-loop filter for the second set of reconstructed samples; providing the first set of reconstructed samples and the second set of reconstructed samples as input to a convolutional cross-component model filter; applying the convolutional cross-component model (CCCM) filter to the first and second set of reconstructed samples to obtain an additional input for reconstructing the second set of samples; applying a cross-component adaptive in-loop filter for outputs of the first adaptive in-loop filter and the second adaptive in-loop filter; and providing an output of the cross-component adaptive in-loop filter to the output of the second adaptive in-loop filter as an additional correction for the second set of samples.

Description

[0001] AN APPARATUS, A METHOD AND A COMPUTER PROGRAM FOR VIDEO CODING AND DECODING TECHNICAL FIELD The present invention relates to an apparatus, a method and a computer program for video coding and decoding. BACKGROUND In video coding, video and image samples are typically encoded using color representations such as YUV or YCbCr consisting of one luminance (luma) and two chrominance (chroma) channels. In these cases the luminance channel, representing mostly the illumination of the scene, is typically coded at certain resolution, while the chrominance channels, representing typically differences between certain color components, are often coded at a second resolution lower than that of the luminance signal. The intention of this kind of a differential representation is to decorrelate the color components and be able to compress the data more efficiently. Adaptive in-loop filters (ALF) perform luma and chroma filtering in parallel fashion to lower the mean square error (MSE) between the reconstruction and the original samples. Forexample, in Versatile Video Coding (VVC) (MPEG-I Part 3), a.k.a. ITU-T H.266, the ALF firstfilters both luma and chroma in parallel, and subsequently also applies cross-component filtering (CC-ALF) to further improve the chroma. Only the luma samples are used as input to the CC- ALF in VVC. The chroma ALF uses chroma reconstruction buffer. However, using luma samples as an input to CC-ALF and / or chroma reconstruction buffers for refining the chroma components may not be optimal all cases. SUMMARY Now in order to at least alleviate the above problems, an enhanced method isintroduced herein. The scope of protection sought for various embodiments of the invention is set out by the independent claims. The embodiments and features, if any, described in this specification that do not fall under the scope of the independent claims are to be interpreted as examples useful for understanding various embodiments of the invention. An apparatus according to a first aspect comprises means for obtaining a first set ofreconstructed samples of a first color channel of an image; means for obtaining a second set ofreconstructed samples of a second color channel of the image; means for applying a firstadaptive in-loop filter for the first set of reconstructed samples; means for applying a secondadaptive in-loop filter for the second set of reconstructed samples; means for providing the firstset of reconstructed samples and the second set of reconstructed samples as input to a convolutional cross-component model filter; means for applying the convolutional cross- component model (CCCM) filter to the first and second set of reconstructed samples to obtain anadditional input for reconstructing the second set of samples; means for applying a cross-component adaptive in-loop filter for outputs of the first adaptive in-loop filter and the secondadaptive in-loop filter; and means for providing an output of the cross-component adaptive in-loop filter to the output of the second adaptive in-loop filter as an additional correction for the second set of samples. According to an embodiment, the apparatus comprises means for providing theadditional input to the second adaptive in-loop filter. According to an embodiment, the apparatus comprises means for providing theadditional input to the cross-component adaptive in-loop filter. According to an embodiment, the apparatus comprises means for performing, by saidconvolutional cross-component model filter, CCCM filter derivation for obtaining filtercoefficients for the samples; and means for applying CCCM filtering using the filter coefficients.According to an embodiment, the apparatus comprises means for providing an outputof the first adaptive in-loop filter as an input to the CCCM filtering. According to an embodiment, the apparatus comprises means for providing an outputof the first adaptive in-loop filter as an input to the cross-component adaptive in-loop filter. According to an embodiment, the apparatus comprises means for providing additionalfilter coefficients and clipping values for the second adaptive in-loop filter and / or the cross- component adaptive in-loop filter, wherein said additional filter coefficients and clipping values are derived from neighboring samples of the current input sample.According to an embodiment, the apparatus comprises means for deriving saidadditional filter coefficients and clipping values using a 3x3 diamond shape filter. According to an embodiment, the first set of reconstructed samples of the first color channel comprise luma components, and the second set of reconstructed samples of the second color channel comprise chroma components. An apparatus according to a second aspect comprises at least one processor and at least one memory, said at least one memory stored with code thereon, which when executed bysaid at least one processor, causes the apparatus to perform at least: obtain a first set ofreconstructed samples of a first color channel of an image; obtain a second set of reconstructedsamples of a second color channel of the image; apply a first adaptive in-loop filter for the firstset of reconstructed samples; apply a second adaptive in-loop filter for the second set ofreconstructed samples; provide the first set of reconstructed samples and the second set ofreconstructed samples as input to a convolutional cross-component model filter; apply the convolutional cross-component model (CCCM) filter to the first and second set of reconstructedsamples to obtain an additional input for reconstructing the second set of samples; apply a cross-component adaptive in-loop filter for outputs of the first adaptive in-loop filter and the secondadaptive in-loop filter; and provide an output of the cross-component adaptive in-loop filter tothe output of the second adaptive in-loop filter as an additional correction for the second set of samples. Amethod according to a third aspect comprises obtaining a first set of reconstructedsamples of a first color channel of an image; obtaining a second set of reconstructed samples of asecond color channel of the image; applying a first adaptive in-loop filter for the first set ofreconstructed samples; applying a second adaptive in-loop filter for the second set ofreconstructed samples; providing the first set of reconstructed samples and the second set ofreconstructed samples as input to a convolutional cross-component model filter; applying the convolutional cross-component model (CCCM) filter to the first and second set of reconstructedsamples to obtain an additional input for reconstructing the second set of samples; applying across-component adaptive in-loop filter for outputs of the first adaptive in-loop filter and thesecond adaptive in-loop filter; and providing an output of the cross-component adaptive in-loopfilter to the output of the second adaptive in-loop filter as an additional correction for the second set of samples.The apparatuses and the computer readable storage mediums stored with code thereon,as described above, are thus arranged to carry out the above methods and one or more of theembodiments related thereto. BRIEF DESCRIPTION OF THE DRAWINGS For better understanding of the present invention, reference will now be made by way of example to the accompanying drawings in which: Figures 1a and 1b show schematically an encoder and a decoder, respectively, suitablefor implementing embodiments of the invention; Figure 2 illustrates locations of the samples used for derivation of parameters for a Cross-Component Linear Model (CCLM); Figures 3a and 3b show examples of classification of luma samples into two classes in the sample domain, and in the spatial domain, respectively; Figure 4 shows an example of co-located reference sample areas consisting ofreconstructed luma and chroma samples defined for both luma and chroma for a ConvolutionalCross-Component Model (CCCM); Figure 5 shows various examples of the dimensions of the filter kernel in CCCM;Figure 6 illustrates an example of four reference lines neighboring to a predictionblock; Figure 7 illustrates a matrix weighted intra prediction process; Figure 8 shows an example of combined inter / intra prediction (CIIP) mode applied to the current coding unit; Figure 9 shows examples of two diamond filter shapes used in VVC; Figure 10 shows examples of subsampled positions used for gradient calculation of alldirections; Figure 11 shows an example of a system level diagram of the CC-ALF process withrespect to the SAO, luma ALF and chroma ALF processes; Figure 12 shows a flow chart of a method for chroma filtering according to anembodiment of the invention; Figure 13 shows an example of filtering pipeline according to an embodiment of theinvention;Figure 14 shows an example of filtering pipeline according to another embodiment ofthe invention; Figure 15 shows an example of a linear diamond shaped filter usable in embodiments of the invention; Figure 16 shows schematically an electronic device employing embodiments of theinvention; Figure 17 shows schematically a user equipment suitable for employing embodimentsof the invention; Figure 18 further shows schematically electronic devices suitable for employingembodiments of the invention connected using wireless and wired network connections; andFigure 19 shows a schematic diagram of an example multimedia communicationsystem within which various embodiments may be implemented. DETAILED DESCRIPTON OF SOME EXAMPLE EMBODIMENTS Video codec consists of an encoder that transforms the input video into a compressed representation suited for storage / transmission and a decoder that can uncompress the compressed video representation back into a viewable form. A video encoder and / or a video decoder mayalso be separate from each other, i.e. need not form a codec. Typically, an encoder discards someinformation in the original video sequence in order to represent the video in a more compact form (that is, at lower bitrate). Typical hybrid video encoders, for example many encoder implementations of ITU-TH.263 and H.264, encode the video information in two phases. Firstly, pixel values in a certainpicture area (or “block”) are predicted for example by motion compensation means (finding and indicating an area in one of the previously coded video frames that corresponds closely to the block being coded) or by spatial means (using the pixel values around the block to be coded in a specified manner). Secondly the prediction error, i.e. the difference between the predicted block of pixels and the original block of pixels, is coded. This is typically done by transforming the difference in pixel values using a specified transform (e.g. Discrete Cosine Transform (DCT) or a variant of it), quantizing the coefficients and entropy coding the quantized coefficients. By varying the fidelity of the quantization process, encoder can control the balance between the accuracy of the pixel representation (picture quality) and size of the resulting coded video representation (file size or transmission bitrate). In temporal prediction, the sources of prediction are previously decoded pictures (a.k.a. reference pictures). In intra block copy (IBC; a.k.a. intra-block-copy prediction),prediction is applied similarly to temporal prediction, but the reference picture is the currentpicture and only previously decoded samples can be referred in the prediction process. Inter- layer or inter-view prediction may be applied similarly to temporal prediction, but the reference picture is a decoded picture from another scalable layer or from another view, respectively. In some cases, inter prediction may refer to temporal prediction only, while in other cases inter prediction may refer collectively to temporal prediction and any of intra block copy, inter-layer prediction, and inter-view prediction provided that they are performed with the same or similar process than temporal prediction. Inter prediction or temporal prediction may sometimes be referred to as motion compensation or motion-compensated prediction. Motion compensation can be performed either with full sample or sub-sample accuracy. In the case of full sample accurate motion compensation, motion can be represented as a motion vector with integer values for horizontal and vertical displacement and the motion compensation process effectively copies samples from the reference picture using thosedisplacements. In the case of sub-sample accurate motion compensation, motion vectors arerepresented by fractional or decimal values for the horizontal and vertical components of the motion vector. In the case a motion vector is referring to a non-integer position in the reference picture, a sub-sample interpolation process is typically invoked to calculate predicted sample values based on the reference samples and the selected sub-sample position. The sub-sample interpolation process typically consists of horizontal filtering compensating for horizontal offsets with respect to full sample positions followed by vertical filtering compensating for vertical offsets with respect to full sample positions. However, the vertical processing can also be done before horizontal processing in some environments. Inter prediction, which may also be referred to as temporal prediction, motion compensation, or motion-compensated prediction, reduces temporal redundancy. In inter prediction the sources of prediction are previously decoded pictures. Intra prediction utilizes the fact that adjacent pixels within the same picture are likely to be correlated. Intra prediction can be performed in spatial or transform domain, i.e., either sample values or transform coefficients can be predicted. Intra prediction is typically exploited in intra coding, where no inter prediction is applied. One outcome of the coding procedure is a set of coding parameters, such as motion vectors and quantized transform coefficients. Many parameters can be entropy-coded more efficiently if they are predicted first from spatially or temporally neighboring parameters. For example, a motion vector may be predicted from spatially adjacent motion vectors and only the difference relative to the motion vector predictor may be coded. Prediction of coding parameters and intra prediction may be collectively referred to as in-picture prediction. Figs.1a and 1b show an encoder and a decoder suitable for employing embodiments of the invention. A video codec consists of an encoder that transforms an input video into a compressed representation suited for storage / transmission and a decoder that can decompress the compressed video representation back into a viewable form. Typically, the encoder discards and / or loses some information in the original video sequence in order to represent the video in a more compact form (that is, at lower bitrate). An example of an encoding process is illustrated in Figure 1a. Figure 4a illustrates an image to be encoded (In); a predicted representation of an image block (P'n); a prediction error signal (Dn); a reconstructed prediction error signal (D'n); a preliminary reconstructed image (I'n); a final reconstructed image (R'n); a transform (T) and inverse transform (T-1); a quantization (Q) and inverse quantization (Q-1); entropy encoding (E); a reference frame memory (RFM); inter prediction (Pinter); intra prediction (Pintra); mode selection (MS) and filtering (F). An example of a decoding process is illustrated in Figure 1b. Figure 1b illustrates a predicted representation of an image block (P'n); a reconstructed prediction error signal (D'n); a preliminary reconstructed image (I'n); a final reconstructed image (R'n); an inverse transform (T-1); an inverse quantization (Q-1); an entropy decoding (E-1); a reference frame memory (RFM); a prediction (either inter or intra) (P); and filtering (F). Many hybrid video encoders encode the video information in two phases. Firstly pixel values in a certain picture area (or “block”) are predicted for example by motion compensation means (finding and indicating an area in one of the previously coded video frames that corresponds closely to the block being coded) or by spatial means (using the pixel values around the block to be coded in a specified manner). Secondly the prediction error, i.e. the difference between the predicted block of pixels and the original block of pixels, is coded. This is typically done by transforming the difference in pixel values using a specified transform (e.g. Discrete Cosine Transform (DCT) or a variant of it), quantizing the coefficients and entropy coding the quantized coefficients. By varying the fidelity of the quantization process, encoder can control the balance between the accuracy of the pixel representation (picture quality) and size of the resulting coded video representation (file size or transmission bitrate). Video codecs may also provide a transform skip mode, which the encoders may choose to use. In the transform skip mode, the prediction error is coded in a sample domain, for example by deriving a sample-wise difference value relative to certain adjacent samples and coding the sample-wise difference value with an entropy coder. Entropy coding / decoding may be performed in many ways. For example, context- based coding / decoding may be applied, where in both the encoder and the decoder modify the context state of a coding parameter based on previously coded / decoded coding parameters. Context-based coding may for example be context adaptive binary arithmetic coding (CABAC) or context-based variable length coding (CAVLC) or any similar entropy coding. Entropy coding / decoding may alternatively or additionally be performed using a variable length coding scheme, such as Huffman coding / decoding or Exp-Golomb coding / decoding. Decoding of coding parameters from an entropy-coded bitstream or codewords may be referred to as parsing. The phrase along the bitstream (e.g. indicating along the bitstream) may be defined to refer to out-of-band transmission, signalling, or storage in a manner that the out-of-band data isassociated with the bitstream. The phrase decoding along the bitstream or alike may refer todecoding the referred out-of-band data (which may be obtained from out-of-band transmission, signalling, or storage) that is associated with the bitstream. For example, an indication along the bitstream may refer to metadata in a container file that encapsulates the bitstream. The H.264 / AVC standard was developed by the Joint Video Team (JVT) of the Video Coding Experts Group (VCEG) of the Telecommunications Standardization Sector of International Telecommunication Union (ITU-T) and the Moving Picture Experts Group (MPEG) of International Organisation for Standardization (ISO) / International Electrotechnical Commission (IEC). The H.264 / AVC standard is published by both parent standardization organizations, and it is referred to as ITU-T Recommendation H.264 and ISO / IEC International Standard 14496-10, also known as MPEG-4 Part 10 Advanced Video Coding (AVC). There have been multiple versions of the H.264 / AVC standard, integrating new extensions or features to the specification. These extensions include Scalable Video Coding (SVC) and Multiview Video Coding (MVC). Version 1 of the High Efficiency Video Coding (H.265 / HEVC a.k.a. HEVC) standardwas developed by the Joint Collaborative Team – Video Coding (JCT-VC) of VCEG andMPEG. The standard was published by both parent standardization organizations, and it isreferred to as ITU-T Recommendation H.265 and ISO / IEC International Standard 23008-2, alsoknown as MPEG-H Part 2 High Efficiency Video Coding (HEVC). Later versions ofH.265 / HEVC included scalable, multiview, fidelity range, three-dimensional, and screen contentcoding extensions which may be abbreviated SHVC, MV-HEVC, REXT, 3D-HEVC, and SCC, respectively. Versatile Video Coding (VVC) (MPEG-I Part 3), a.k.a. ITU-T H.266, is a videocompression standard developed by the Joint Video Experts Team (JVET) of the Moving PictureExperts Group (MPEG), (formally ISO / IEC JTC1 SC29 WG11) and Video Coding ExpertsGroup (VCEG) of the International Telecommunication Union (ITU) to be the successor toHEVC / H.265. Some key definitions, bitstream and coding structures, and concepts of H.264 / AVC and HEVC are described in this section for providing background for a video encoder, decoder, encoding method, decoding method, and a bitstream structure, wherein the embodiments may be implemented. Some of the key definitions, bitstream and coding structures, and concepts ofH.264 / AVC are the same as in HEVC – hence, they are described below jointly.Similarly to many earlier video coding standards, the bitstream syntax and semantics as well as the decoding process for error-free bitstreams are specified in H.264 / AVC and HEVC.The encoding process is not specified, but encoders must generate conforming bitstreams.Bitstream and decoder conformance can be verified with the Hypothetical Reference Decoder (HRD). The standards contain coding tools that help in coping with transmission errors and losses, but the use of the tools in encoding is optional and no decoding process has been specified for erroneous bitstreams. The elementary unit for the input to an H.264 / AVC or HEVC encoder and the output of an H.264 / AVC or HEVC decoder, respectively, is a picture. A picture given as an input to an encoder may also be referred to as a source picture, and a picture decoded by a decoded may be referred to as a decoded picture. The source and decoded pictures are each comprised of one or more sample arrays, such as one of the following sets of sample arrays: -Luma (Y) only (monochrome).- Luma and two chroma (YCbCr or YCgCo).- Green, Blue and Red (GBR, also known as RGB).- Arrays representing other unspecified monochrome or tri-stimulus color samplings (forexample, YZX, also known as XYZ). Typically, video is encoded in YUV or YCbCr color space as that is found to reflectsome characteristics of human visual system and allows using lower quality representation for Cb and Cr channels as human perception is less sensitive to the chrominance fidelity those channels represent. In H.264 / AVC and HEVC, a picture may either be a frame or a field. A frame comprises a matrix of luma samples and possibly the corresponding chroma samples. A field is a set of alternate sample rows of a frame and may be used as encoder input, when the source signal is interlaced. Chroma sample arrays may be absent (and hence monochrome sampling may be in use) or chroma sample arrays may be subsampled when compared to luma sample arrays. Chroma formats may be summarized as follows: -In monochrome sampling there is only one sample array, which may be nominallyconsidered the luma array. -In 4:2:0 sampling, each of the two chroma arrays has half the height and half the width ofthe luma array. -In 4:2:2 sampling, each of the two chroma arrays has the same height and half the widthof the luma array. -In 4:4:4 sampling when no separate color planes are in use, each of the two chromaarrays has the same height and width as the luma array. In H.264 / AVC and HEVC, it is possible to code sample arrays as separate color planes into the bitstream and respectively decode separately coded color planes from the bitstream. When separate color planes are in use, each one of them is separately processed (by the encoder and / or the decoder) as a picture with monochrome sampling. A partitioning may be defined as a division of a set into subsets such that each element of the set is in exactly one of the subsets. When describing the operation of HEVC encoding and / or decoding, the following terms may be used. A coding block may be defined as an NxN block of samples for some value of N such that the division of a coding tree block into coding blocks is a partitioning. A coding tree block (CTB) may be defined as an NxN block of samples for some value of N such that the division of a component into coding tree blocks is a partitioning. A coding tree unit (CTU) may be defined as a coding tree block of luma samples, two corresponding coding tree blocks of chroma samples of a picture that has three sample arrays, or a coding tree block of samples of a monochrome picture or a picture that is coded using three separate color planes and syntax structures used to code the samples. A coding unit (CU) may be defined as a coding block of luma samples, two corresponding coding blocks of chroma samples of a picture that has three sample arrays, or a coding block of samples of a monochrome picture or a picture that is codedusing three separate color planes and syntax structures used to code the samples. A CU with themaximum allowed size may be named as LCU (largest coding unit) or coding tree unit (CTU) and the video picture is divided into non-overlapping LCUs. A CU consists of one or more prediction units (PU) defining the prediction process for the samples within the CU and one or more transform units (TU) defining the prediction error coding process for the samples in the said CU. Typically, a CU consists of a square block of samples with a size selectable from a predefined set of possible CU sizes. Each PU and TU canbe further split into smaller PUs and TUs in order to increase granularity of the prediction andprediction error coding processes, respectively. Each PU has prediction information associated with it defining what kind of a prediction is to be applied for the pixels within that PU (e.g.motion vector information for inter predicted PUs and intra prediction directionality informationfor intra predicted PUs).Each TU can be associated with information describing the prediction error decoding process for the samples within the said TU (including e.g. DCT coefficient information). It is typically signalled at CU level whether prediction error coding is applied or not for each CU. In the case there is no prediction error residual associated with the CU, it can be considered thereare no TUs for the said CU. The division of the image into CUs, and division of CUs into PUsand TUs is typically signalled in the bitstream allowing the decoder to reproduce the intendedstructure of these units. To be able to utilize parallel processing, images can be split into independently codable and decodable image segments (slices or tiles). In HEVC, a picture can be partitioned in tiles, which are rectangular and contain an integer number of LCUs. In HEVC, the partitioning to tiles forms a regular grid, where heights and widths of tiles differ from each other by one LCU at the maximum. In HEVC, a slice is defined to be an integer number of coding tree units contained in one independent slice segment and all subsequent dependent slice segments (if any) that precede the next independent slice segment (if any) within the same access unit. In HEVC, a slice segment is defined to be an integer number of coding tree units ordered consecutively in the tile scan and contained in a single NAL unit. The division of each picture into slice segments is a partitioning. In HEVC, an independent slice segment is defined to be a slice segment for which the values of the syntax elements of the slice segment header are not inferred from the values for a preceding slice segment, and a dependent slice segment is defined to be a slice segment for which the values of some syntax elements of the slice segment header are inferred from the values for the preceding independent slice segment in decoding order. In HEVC, a slice header is defined to be the slice segment header of the independent slice segment that is a current slice segment or is the independent slice segment that precedes a current dependent slice segment, and a slice segment header is defined to be a part of a coded slice segment containing the dataelements pertaining to the first or all coding tree units represented in the slice segment. The CUsare scanned in the raster scan order of LCUs within tiles or within a picture, if tiles are not in use.Within an LCU, the CUs have a specific scan order.The decoder reconstructs the output video by applying prediction means similar to the encoder to form a predicted representation of the pixel blocks (using the motion or spatial information created by the encoder and stored in the compressed representation) and prediction error decoding (inverse operation of the prediction error coding recovering the quantized prediction error signal in spatial pixel domain). After applying prediction and prediction error decoding means the decoder sums up the prediction and prediction error signals (pixel values) to form the output video frame. The decoder (and encoder) can also apply additional filtering means to improve the quality of the output video before passing it for display and / or storing it as prediction reference for the forthcoming frames in the video sequence. Instead, or in addition to approaches utilizing sample value prediction and transform coding for indicating the coded sample values, a color palette based coding can be used. Palette based coding refers to a family of approaches for which a palette, i.e. a set of colors and associated indexes, is defined and the value for each sample within a coding unit is expressed by indicating its index in the palette. Palette based coding can typically achieve good coding efficiency in coding units with a relatively small number of colors (such as image areas which are representing computer screen content, like text or simple graphics). In order to improve the coding efficiency of palette coding different kinds of palette index prediction approaches can be utilized, or the palette indexes can be run-length coded to be able to represent larger homogenous image areas efficiently. Also, in the case the CU contains sample values that are not recurring within the CU, escape coding can be utilized. Escape coded samples are transmitted without referring to any of the palette indexes. Instead, their values are indicated individually for each escape coded sample. The filtering may for example include one more of the following: deblocking, sampleadaptive offset (SAO), and / or adaptive loop filtering (ALF). H.264 / AVC includes a deblocking,whereas HEVC includes both deblocking and SAO. In typical video codecs the motion information is indicated with motion vectors associated with each motion compensated image block, such as a prediction unit. Each of these motion vectors represents the displacement of the image block in the picture to be coded (in the encoder side) or decoded (in the decoder side) and the prediction source block in one of the previously coded or decoded pictures. In order to represent motion vectors efficiently those are typically coded differentially with respect to block specific predicted motion vectors. In typical video codecs the predicted motion vectors are created in a predefined way, for example calculating the median of the encoded or decoded motion vectors of the adjacent blocks. Another way to create motion vector predictions is to generate a list of candidate predictions from adjacent blocks and / or co-located blocks in temporal reference pictures and signalling the chosen candidate as the motion vector predictor. In addition to predicting the motion vector values, it can be predicted which reference picture(s) are used for motion-compensated prediction and this prediction information may be represented for example by a reference index of previously coded / decoded picture. The reference index is typically predicted from adjacent blocks and / or co-located blocks in temporal reference picture. Moreover, typical high efficiency video codecs employ an additional motion information coding / decoding mechanism, often called merging / merge mode, where all the motion field information, which includes motion vector and corresponding reference picture index for each available reference picture list, is predicted and used without any modification / correction. Similarly, predicting the motion field information is carried out using the motion field information of adjacent blocks and / or co-located blocks in temporal reference pictures and the used motion field information is signalled among a list of motion field candidate list filled with motion field information of available adjacent / co-located blocks. In typical video codecs the prediction residual after motion compensation is first transformed with a transform kernel (like DCT) and then coded. The reason for this is that often there still exists some correlation among the residual and transform can in many cases help reduce this correlation and provide more efficient coding. Video coding standards and specifications may allow encoders to divide a coded picture to coded slices or alike. In-picture prediction is typically disabled across slice boundaries. Thus, slices can be regarded as a way to split a coded picture to independently decodable pieces. In H.264 / AVC and HEVC, in-picture prediction may be disabled across slice boundaries. Thus, slices can be regarded as a way to split a coded picture into independently decodable pieces, and slices are therefore often regarded as elementary units for transmission. In many cases, encoders may indicate in the bitstream which types of in-picture prediction are turned off across slice boundaries, and the decoder operation takes this information into account for example when concluding which prediction sources are available. For example, samples from a neighboring CU may be regarded as unavailable for intra prediction, if the neighboring CU resides in a different slice. An elementary unit for the output of an H.264 / AVC or HEVC encoder and the input of an H.264 / AVC or HEVC decoder, respectively, is a Network Abstraction Layer (NAL) unit. For transport over packet-oriented networks or storage into structured files, NAL units may be encapsulated into packets or similar structures. A bytestream format has been specified in H.264 / AVC and HEVC for transmission or storage environments that do not provide framing structures. The bytestream format separates NAL units from each other by attaching a start code in front of each NAL unit. To avoid false detection of NAL unit boundaries, encoders run a byte- oriented start code emulation prevention algorithm, which adds an emulation prevention byte to the NAL unit payload if a start code would have occurred otherwise. In order to enablestraightforward gateway operation between packet- and stream-oriented systems, start code emulation prevention may always be performed regardless of whether the bytestream format is in use or not. A NAL unit may be defined as a syntax structure containing an indication of the type of data to follow and bytes containing that data in the form of an RBSP interspersed as necessary with emulation prevention bytes. A raw byte sequence payload (RBSP) may be defined as a syntax structure containing an integer number of bytes that is encapsulated in a NAL unit. An RBSP is either empty or has the form of a string of data bits containing syntax elements followed by an RBSP stop bit and followed by zero or more subsequent bits equal to 0. NAL units consist of a header and payload. In H.264 / AVC and HEVC, the NAL unit header indicates the type of the NAL unit. In HEVC, a two-byte NAL unit header is used for all specified NAL unit types. The NAL unit header contains one reserved bit, a six-bit NAL unit type indication, a three-bit nuh_temporal_id_plus1 indication for temporal level (may be required to be greater than or equal to 1) and a six-bit nuh_layer_id syntax element. The temporal_id_plus1 syntax element may be regarded as a temporal identifier for the NAL unit, and a zero-based TemporalId variable may bederived as follows: TemporalId = temporal_id_plus1 – 1. The abbreviation TID may be used tointerchangeably with the TemporalId variable. TemporalId equal to 0 corresponds to the lowest temporal level. The value of temporal_id_plus1 is required to be non-zero in order to avoid start code emulation involving the two NAL unit header bytes. The bitstream created by excluding all VCL NAL units having a TemporalId greater than or equal to a selected value and including all other VCL NAL units remains conforming. Consequently, a picture having TemporalId equal to tid_value does not use any picture having a TemporalId greater than tid_value as inter prediction reference. A sub-layer or a temporal sub-layer may be defined to be a temporal scalable layer (or a temporal layer, TL) of a temporal scalable bitstream, consisting of VCL NAL units with a particular value of the TemporalId variable and the associated non-VCL NAL units. nuh_layer_id can be understood as a scalability layer identifier. NAL units can be categorized into Video Coding Layer (VCL) NAL units and non-VCL NAL units. VCL NAL units are typically coded slice NAL units. In HEVC, VCL NALunits contain syntax elements representing one or more CU. A non-VCL NAL unit may be for example one of the following types: a sequence parameter set, a picture parameter set, a supplemental enhancement information (SEI) NAL unit, an access unit delimiter, an end of sequence NAL unit, an end of bitstream NAL unit, or a filler data NAL unit. Parameter sets may be needed for the reconstruction of decoded pictures, whereas many of the other non-VCL NAL units are not necessary for the reconstruction of decoded sample values. Parameters that remain unchanged through a coded video sequence may be included in a sequence parameter set. In addition to the parameters that may be needed by the decoding process, the sequence parameter set may optionally contain video usability information (VUI), which includes parameters that may be important for buffering, picture output timing, rendering,and resource reservation. In HEVC a sequence parameter set RBSP includes parameters that canbe referred to by one or more picture parameter set RBSPs or one or more SEI NAL units containing a buffering period SEI message. A picture parameter set contains such parameters that are likely to be unchanged in several coded pictures. A picture parameter set RBSP may include parameters that can be referred to by the coded slice NAL units of one or more coded pictures. In HEVC, a video parameter set (VPS) may be defined as a syntax structure containing syntax elements that apply to zero or more entire coded video sequences as determined by the content of a syntax element found in the SPS referred to by a syntax element found in the PPS referred to by a syntax element found in each slice segment header. A video parameter set RBSP may include parameters that can be referred to by one or more sequence parameter set RBSPs. The relationship and hierarchy between video parameter set (VPS), sequence parameter set (SPS), and picture parameter set (PPS) may be described as follows. VPS resides one level above SPS in the parameter set hierarchy and in the context of scalability and / or 3D video. VPS may include parameters that are common for all slices across all (scalability or view) layers in the entire coded video sequence. SPS includes the parameters that are common for all slices in a particular (scalability or view) layer in the entire coded video sequence, and may be shared by multiple (scalability or view) layers. PPS includes the parameters that are common for all slices in a particular layer representation (the representation of one scalability or view layer in one access unit) and are likely to be shared by all slices in multiple layer representations. VPS may provide information about the dependency relationships of the layers in a bitstream, as well as many other information that are applicable to all slices across all (scalability or view) layers in the entire coded video sequence. VPS may be considered to comprise two parts, the base VPS and a VPS extension, where the VPS extension may be optionally present. Out-of-band transmission, signaling or storage can additionally or alternatively be used for other purposes than tolerance against transmission errors, such as ease of access or session negotiation. For example, a sample entry of a track in a file conforming to the ISO Base Media File Format may comprise parameter sets, while the coded data in the bitstream is stored elsewhere in the file or in another file. The phrase along the bitstream (e.g. indicating along the bitstream) or along a coded unit of a bitstream (e.g. indicating along a coded tile) may be used in claims and described embodiments to refer to out-of-band transmission, signaling, or storage in amanner that the out-of-band data is associated with the bitstream or the coded unit, respectively.The phrase decoding along the bitstream or along a coded unit of a bitstream or alike may referto decoding the referred out-of-band data (which may be obtained from out-of-bandtransmission, signaling, or storage) that is associated with the bitstream or the coded unit,respectively. A SEI NAL unit may contain one or more SEI messages, which are not required for the decoding of output pictures but may assist in related processes, such as picture output timing, rendering, error detection, error concealment, and resource reservation. A coded picture is a coded representation of a picture. In HEVC, a coded picture may be defined as a coded representation of a picture containing all coding tree units of the picture. In HEVC, an access unit (AU) may be defined as a set of NAL units that are associated with each other according to a specified classification rule, are consecutive in decoding order, and contain at most one picture with any specific value of nuh_layer_id. In addition to containing the VCL NAL units of the coded picture, an access unit may also contain non-VCL NAL units. Said specified classification rule may for example associate pictures with the same output time or picture output count value into the same access unit. A bitstream may be defined as a sequence of bits, in the form of a NAL unit stream or a byte stream, that forms the representation of coded pictures and associated data forming one or more coded video sequences. A first bitstream may be followed by a second bitstream in the same logical channel, such as in the same file or in the same connection of a communication protocol. An elementary stream (in the context of video coding) may be defined as a sequence of one or more bitstreams. The end of the first bitstream may be indicated by a specific NAL unit, which may be referred to as the end of bitstream (EOB) NAL unit and which is the last NAL unit of the bitstream. In HEVC and its current draft extensions, the EOB NAL unit is required to have nuh_layer_id equal to 0. In H.264 / AVC, a coded video sequence is defined to be a sequence of consecutive access units in decoding order from an IDR access unit, inclusive, to the next IDR access unit, exclusive, or to the end of the bitstream, whichever appears earlier. In HEVC, a coded video sequence (CVS) may be defined, for example, as a sequence of access units that consists, in decoding order, of an IRAP access unit with NoRaslOutputFlagequal to 1, followed by zero or more access units that are not IRAP access units withNoRaslOutputFlag equal to 1, including all subsequent access units up to but not including any subsequent access unit that is an IRAP access unit with NoRaslOutputFlag equal to 1. An IRAP access unit may be defined as an access unit in which the base layer picture is an IRAP picture. The value of NoRaslOutputFlag is equal to 1 for each IDR picture, each BLA picture, and eachIRAP picture that is the first picture in that particular layer in the bitstream in decoding order, isthe first IRAP picture that follows an end of sequence NAL unit having the same value of nuh_layer_id in decoding order. There may be means to provide the value of HandleCraAsBlaFlag to the decoder from an external entity, such as a player or a receiver, which may control the decoder. HandleCraAsBlaFlag may be set to 1 for example by a player that seeks to a new position in a bitstream or tunes into a broadcast and starts decoding and then starts decoding from a CRA picture. When HandleCraAsBlaFlag is equal to 1 for a CRA picture, the CRA picture is handled and decoded as if it were a BLA picture. In HEVC, a coded video sequence may additionally or alternatively (to the specification above) be specified to end, when a specific NAL unit, which may be referred to asan end of sequence (EOS) NAL unit, appears in the bitstream and has nuh_layer_id equal to 0.A group of pictures (GOP) and its characteristics may be defined as follows. A GOP can be decoded regardless of whether any previous pictures were decoded. An open GOP is such a group of pictures in which pictures preceding the initial intra picture in output order might not be correctly decodable when the decoding starts from the initial intra picture of the open GOP. In other words, pictures of an open GOP may refer (in inter prediction) to pictures belonging to a previous GOP. An HEVC decoder can recognize an intra picture starting an open GOP, because a specific NAL unit type, CRA NAL unit type, may be used for its coded slices. A closed GOP is such a group of pictures in which all pictures can be correctly decoded when the decoding starts from the initial intra picture of the closed GOP. In other words, no picture in a closed GOP refers to any pictures in previous GOPs. In H.264 / AVC and HEVC, a closed GOP may start from an IDR picture. In HEVC a closed GOP may also start from a BLA_W_RADL or a BLA_N_LP picture. An open GOP coding structure is potentially more efficient in the compression compared to a closed GOP coding structure, due to a larger flexibility in selection of reference pictures. A Decoded Picture Buffer (DPB) may be used in the encoder and / or in the decoder. There are two reasons to buffer decoded pictures, for references in inter prediction and for reordering decoded pictures into output order. As H.264 / AVC and HEVC provide a great deal of flexibility for both reference picture marking and output reordering, separate buffers for reference picture buffering and output picture buffering may waste memory resources. Hence, the DPB may include a unified decoded picture buffering process for reference pictures and output reordering. A decoded picture may be removed from the DPB when it is no longer used as a reference and is not needed for output. In many coding modes of H.264 / AVC and HEVC, the reference picture for inter prediction is indicated with an index to a reference picture list. The index may be coded with variable length coding, which usually causes a smaller index to have a shorter value for the corresponding syntax element. In H.264 / AVC and HEVC, two reference picture lists (reference picture list 0 and reference picture list 1) are generated for each bi-predictive (B) slice, and one reference picture list (reference picture list 0) is formed for each inter-coded (P) slice. Many coding standards, including H.264 / AVC and HEVC, may have decoding process to derive a reference picture index to a reference picture list, which may be used to indicate which one of the multiple reference pictures is used for inter prediction for a particular block. A reference picture index may be coded by an encoder into the bitstream is some inter coding modes or it may be derived (by an encoder and a decoder) for example using neighboring blocks in some other inter coding modes. HEVC comprises 35 intra prediction modes, including a DC, a planar, and 33 angular (directional) prediction modes. The DC and the planar mode are targeted at flat areas (i.e., the DC mode representing a block whose pixel values are constant across the block) or areas with few structure (i.e., the planar mode representing a block with pixel values gradually changing with a small planar gradient). The angular modes, in turn, provide directional prediction in a very granular way. Motion parameter types or motion information may include but are not limited to one or more of the following types: -an indication of a prediction type (e.g. intra prediction, uni-prediction, bi-prediction)and / or a number of reference pictures; -an indication of a prediction direction, such as inter (a.k.a. temporal) prediction, inter-layer prediction, inter-view prediction, view synthesis prediction (VSP), and inter- component prediction (which may be indicated per reference picture and / or per prediction type and where in some embodiments inter-view and view-synthesis prediction may be jointly considered as one prediction direction) and / or -an indication of a reference picture type, such as a short-term reference picture and / or along-term reference picture and / or an inter-layer reference picture (which may be indicated e.g. per reference picture) -a reference index to a reference picture list and / or any other identifier of a referencepicture (which may be indicated e.g. per reference picture and the type of which may depend on the prediction direction and / or the reference picture type and which may beaccompanied by other relevant pieces of information, such as the reference picture list or alike to which reference index applies); -a horizontal motion vector component (which may be indicated e.g. per prediction blockor per reference index or alike); -a vertical motion vector component (which may be indicated e.g. per prediction block orper reference index or alike); -one or more parameters, such as picture order count difference and / or a relative cameraseparation between the picture containing or associated with the motion parameters and its reference picture, which may be used for scaling of the horizontal motion vector component and / or the vertical motion vector component in one or more motion vector prediction processes (where said one or more parameters may be indicated e.g. per each reference picture or each reference index or alike); -coordinates of a block to which the motion parameters and / or motion information applies,e.g. coordinates of the top-left sample of the block in luma sample units; -extents (e.g. a width and a height) of a block to which the motion parameters and / ormotion information applies. In comparison to the previous video coding standards, Versatile Video Codec(H.266 / VVC) introduces a plurality of new coding tools, such as the following:^ Intra prediction– 67 intra mode with wide angles mode extension– Block size and mode dependent 4 tap interpolation filter– Position dependent intra prediction combination (PDPC)– Cross component linear model intra prediction (CCLM)– Multi-reference line intra prediction– Intra sub-partitions– Weighted intra prediction with matrix multiplication^ Inter-picture prediction– Block motion copy with spatial, temporal, history-based, and pairwise averagemerging candidates –Affine motion inter prediction– sub-block based temporal motion vector prediction– Adaptive motion vector resolution– 8x8 block-based motion compression for temporal motion prediction– High precision (1 / 16 pel) motion vector storage and motion compensation with 8-tap interpolation filter for luma component and 4-tap interpolation filter for chroma component –Triangular partitions– Combined intra and inter prediction– Merge with MVD (MMVD)– Symmetrical MVD coding– Bi-directional optical flow– Decoder side motion vector refinement– Bi-prediction with CU-level weight^ Transform, quantization and coefficients coding– Multiple primary transform selection with DCT2, DST7 and DCT8– Secondary transform for low frequency zone– Sub-block transform for inter predicted residual– Dependent quantization with max QP increased from 51 to 63– Transform coefficient coding with sign data hiding– Transform skip residual coding^ Entropy Coding– Arithmetic coding engine with adaptive double windows probability update^ In loop filter– In-loop reshaping– Deblocking filter with strong longer filter– Sample adaptive offset– Adaptive Loop Filter^ Screen content coding:– Current picture referencing with reference region restriction^ 360-degree video coding– Horizontal wrap-around motion compensation^ High-level syntax and parallel processing– Reference picture management with direct reference picture list signalling– Tile groups with rectangular shape tile groupsThe partitioning in VVC is carried out similarly to HEVC, i.e., each picture is divided into coding tree units (CTUs). A picture may also be divided into slices, tiles, bricks and sub- pictures. CTU may be split into smaller CUs using quaternary tree structure. Each CU may be divided using quad-tree and nested multi-type tree including ternary and binary split. However, there are specific rules to infer partitioning in picture boundaries, and the redundant split patterns are disallowed in nested multi-type partitioning. In the new coding tools listed above, the cross-component linear model (CCLM)prediction mode is used in the VVC to reduce the cross-component redundancy. Therein, thechroma samples are predicted based on the reconstructed luma samples of the same CU by using a linear model as follows: pred^(i, j) = α · rec^′(i, j) + β (Eq. 1a)where pred^(i, j) represents the predicted chroma samples in a CU and rec^'(i, j)represents the downsampled reconstructed luma samples of the same CU. Alternatively, the below equation may be used for CCLM:(Eq. 1b)where >> operation denotes a bit shifting to right by value k. The CCLM parameters (α and β) are derived with at most four neighbouring chromasamples and their corresponding down-sampled luma samples. Suppose the current chroma block dimensions are W×H, then W’ and H’ are set as -W’ = W, H’ = H when LM mode is applied;- W’ =W + H when LM-A mode is applied;- H’ = H + W when LM-L mode is applied;Herein, LM-A mode refers to linear model_above, where only the above template (i.e. sample values from neighbouring positions above the CU) is used to calculate the linear model coefficients. To get more samples, the above template is extended to (W+H). LM-L mode, in turn, refers to linear model_left, where only left template (i.e. sample values from neighbouring positions left to the CU) is used to calculate the linear model coefficients. To get more samples, the left template is extended to (H+W). For a non-square block, the above template is extended to W+W, the left template is extended to H+H. The above neighbouring positions are denoted as S[ 0, −1 ]…S[ W’ − 1, −1 ] and theleft neighbouring positions are denoted as S[ −1, 0 ]…S[ −1, H’ − 1 ]. Then the four samples areselected as -S[W’ / 4, −1 ], S[ 3 * W’ / 4, −1 ], S[ −1, H’ / 4 ], S[ −1, 3 * H’ / 4 ] when LM mode isapplied and both above and left neighbouring samples are available; -S[ W’ / 8, −1 ], S[ 3 * W’ / 8, −1 ], S[ 5 * W’ / 8, −1 ], S[ 7 * W’ / 8, −1 ] when LM-Amode is applied or only the above neighbouring samples are available; -S[ −1, H’ / 8 ], S[ −1, 3 * H’ / 8 ], S[ −1, 5 * H’ / 8 ], S[ −1, 7 * H’ / 8 ] when LM-Lmode is applied or only the left neighbouring samples are available; The four neighbouring luma samples at the selected positions are down-sampled and compared four times to find two smaller values: x0A and x1A, and two larger values: x0B and x1B. Their corresponding chroma sample values are denoted as y0A, y1A, y0B and y1B. Then xA, xB, yA and yB are derived as: Finally, the linear model parameters ^ and ^ are obtained according to the followingequations:^ =^^^^^^^^^^(Eq. 3) β= ^^ − α · ^^ (Eq. 4)Figure 2 shows an example of the location of the left and above samples and thesample of the current block involved in the CCLM mode. The division operation to calculate parameter α is implemented with a look-up table. To reduce the memory required for storing the table, the diff value (difference between maximum and minimum values) and the parameter α are expressed by an exponential notation. For example, diff is approximated with a 4-bit significant part and an exponent. Consequently,the table for 1 / diff is reduced into 16 elements for 16 values of the significant part as follows:DivTable [ ] = { 0, 7, 6, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 1, 1, 0 } (Eq. 5)This provides the benefit of both reducing the complexity of the calculation as well as the memory size required for storing the needed tables. To match the chroma sample locations for 4:2:0 video sequences, two types of downsampling filter are applied to luma samples to achieve 2 to 1 downsampling ratio in both horizontal and vertical directions. The selection of downsampling filter is specified by a SPS level flag. The two downsampling filters are as follows, which are corresponding to “type-0” and “type-2” content, respectively: It is noted that only one luma line (general line buffer in intra prediction) is used to make the down-sampled luma samples when the upper reference line is at the CTU boundary. This parameter computation is performed as part of the decoding process and is not just as an encoder search operation. As a result, no syntax is used to convey the α and β values to the decoder. For chroma intra mode coding, a total of 8 intra modes are allowed for chroma intra mode coding. Those modes include five traditional intra modes and three cross-component linear model modes (CCLM, LM_A, and LM_L). Chroma mode signalling and derivation process are shown in Table 1. Chroma mode coding directly depends on the intra prediction mode of the corresponding luma block. Since separate block partitioning structure for luma and chroma components is enabled in I slices, one chroma block may correspond to multiple luma blocks. Therefore, for Chroma DM mode, the intra prediction mode of the corresponding luma block covering the center position of the current chroma block is directly inherited. Corresponding luma intra prediction mode Chroma prediction mode 050 18 1 X ( 0 <= X <= 66 )0 66 0 0 0 01 50 66 50 50 502 18 18 66 18 183 1 1 1 66 14 0 50 18 1 X5 81 81 81 81 816 82 82 82 82 827 83 83 83 83 83Table 1. A single binarization table is used regardless of the value of sps_cclm_enabled_flag as shown in Table 2. Value of intra_chroma_pred_mode Bin string 4000 01001 01012 01103 01115 106 1107 111Table 2. In Table 2, the first bin indicates whether it is regular (0) or LM modes (1). If it is LM mode, then the next bin indicates whether it is LM_CHROMA (0) or not. If it is not LM_CHROMA, next 1 bin indicates whether it is LM_L (0) or LM_A (1). For this case, when sps_cclm_enabled_flag is 0, the first bin of the binarization table for the corresponding intra_chroma_pred_mode can be discarded prior to the entropy coding. Or, in other words, the first bin is inferred to be 0 and hence not coded. This single binarization table is used for bothsps_cclm_enabled_flag equal to 0 and 1 cases. The first two bins in Table 2 are context codedwith its own context model, and the rest bins are bypass coded. In addition, in order to reduce luma-chroma latency in dual tree, when the 64x64 lumacoding tree node is partitioned with Not Split (and intra sub-partitions (ISP) is not used for the64x64 CU) or QT, the chroma CUs in 32x32 / 32x16 chroma coding tree node are allowed to use CCLM in the following way: -If the 32x32 chroma node is not split or partitioned QT split, all chroma CUs in the 32x32node can use CCLM -If the 32x32 chroma node is partitioned with Horizontal BT, and the 32x16 child nodedoes not split or uses Vertical BT split, all chroma CUs in the 32x16 chroma node can use CCLM. In all the other luma and chroma coding tree split conditions, CCLM is not allowed for chroma CU. Multi-model LM (MMLM) The CCLM included in VVC is extended by adding three Multi-model LM (MMLM) modes. In each MMLM mode, the reconstructed neighbouring samples are classified into two classes using a threshold which is the average of the luma reconstructed neighbouring samples. The linear model of each class is derived using the Least-Mean-Square (LMS) method. For the CCLM mode, the LMS method is also used to derive the linear model. Figures 3a and 3billustrate two luma-to-chroma models obtained for luma (Y) threshold of 17 in sample domainand spatial domain, respectively. Each luma-to-chroma model has its own linear modelparameters α and β. As can be seen in Figure 3b, each luma-to-chroma model corresponds to aspatial segmentation of the content (i.e., they correspond to different objects or textures in the scene). Convolutional cross-component model (CCCM) An improved version of cross-component prediction, known as CCCM, uses 2D filter kernel to derive the luma-to-chroma model. The filter coefficients are derived decoder-side using reconstructed set of input data and chroma samples. For the filter coefficient derivation, co- located reference sample areas (consisting of reconstructed luma and chroma samples) aredefined for both luma and chroma, as shown in Figure 4, where the typically used 4:2:0 chromadown-sampling has been applied. The reference sample area for a given block can be, for example, six lines above and left as shown in Figure 4, yet any number of reference lines (that can be realized by both the encoder and decoder) can be used. Generally, reference samples can contain any chroma and luma samples that have been reconstructed by both the encoder and decoder. Once the reference samples are determined the filter coefficients can be derived, for example, using different types of linear regression tools such as ordinary least-squares estimation, orthogonal matching pursuit, optimized orthogonal matching pursuit, ridge regression, or least absolute shrinkage and selection operator. The dimensions of the filter kernel can be for example 1x3 (1D vertical), 3x1 (1D horizontal), 3x3, 7x7 or any dimensions, and can be shaped (by selecting only a subset of all possible kernel locations) as a cross or a diamond (as shown in Figure 5) or as any given shape. When referring to the samples within the filter kernel the following notation is used: north(above), east (right), south (below), west (left) and center, as illustrated in Figure 5 using theletters N, E, S, W, C. The overall method of reconstructing chroma samples using convolution between a decoder-side obtained filter kernel and a set of input data is referred to as convolutional cross- component model (CCCM) here. The following steps can be applied to perform a CCCM operation: 1) Define co-located reference areas over the luma and chroma components.2) Down-sample the luma samples to match the chroma grid (optional).3) Scan the luma and chroma samples of the reference area and collect available statistics(such as auto-correlation matrix and cross-correlation vector) based on the filter shape. 4) Solve the filter coefficients by minimizing squared-error (or any other metric) based onthe available statistics (such as the auto-correlation matrix and cross-correlation vector). 5) Calculate a predicted chroma block by convolving the down-sampled luma samples withthe filter kernel. Let us define the (possibly down-sampled) luma samples as a 2D array Y(x,y) indexed using horizontal x-coordinate and vertical y-coordinate. Let us also define the co-located chroma samples as a 2D array C(x,y) and the filter kernel (i.e., coefficients) as 3x3 array F(i,j). On a sample level we define the convolution between Y and F as, When using other data terms, such as the non-linear square-root term, the appended convolution becomes,where ^^ are filter coefficients that reside outside of the 2D filter kernel yet have been obtained asa part of the system of linear equations that were used to solve the 2D filter coefficients in Step 4 above. Similarly, we can add the bias term to the convolution with, Multiple reference line (MRL) intra prediction Multiple reference line (MRL) intra prediction uses more reference lines for intra prediction. In Figure 6, an example of 4 reference lines is depicted, where the samples of segments A and F are not fetched from reconstructed neighbouring samples but padded with the closest samples from Segment B and E, respectively. HEVC intra-picture prediction uses the nearest reference line (i.e., reference line 0). In MRL, 2 additional lines (reference line 1 and reference line 3) are used. The index of selected reference line (mrl_idx) is signalled and used to generate intra predictor. For reference line idx, which is greater than 0, only include additional reference line modes in MPM list and only signal mpm index without remaining mode. The reference line index is signalled before intra prediction modes, and Planar mode is excluded from intra prediction modes in case a nonzero reference line index is signalled. MRL is disabled for the first line of blocks inside a CTU to prevent using extended reference samples outside the current CTU line. Also, PDPC is disabled when additional line is used. For MRL mode, the derivation of DC value in DC intra prediction mode for non-zero reference line indices are aligned with that of reference line index 0. MRL requires the storage of 3 neighboring luma reference lines with a CTU to generate predictions. The CCLM tool also requires 3 neighboring luma reference lines for its down-sampling filters. The definition of MLR to use the same 3 lines is aligned as CCLM to reduce the storage requirements for decoders. Intra sub-partitions (ISP) The intra sub-partitions (ISP) divides luma intra-predicted blocks vertically or horizontally into 2 or 4 sub-partitions depending on the block size. For example, minimum block size for ISP is 4x8 (or 8x4). If block size is greater than 4x8 (or 8x4) then the corresponding block is divided by 4 sub-partitions. It has been noted that the M×128 (with M≤64) and 128×N (with N≤64) ISP blocks could generate a potential issue with the 64×64 VDPU. For example, an M×128 CU in the single tree case has an M×128 luma TB and two corresponding M / 2×64 chroma TBs. If the CU uses ISP, then the luma TB will be divided into four M×32 TBs (only the horizontal split is possible), each of them smaller than a 64×64 block. However, in the current design of ISP chroma blocks are not divided. Therefore, both chroma components will have a size greater than a 32×32 block. Analogously, a similar situation could be created with a 128×N CU using ISP. Hence, these two cases are an issue for the 64×64 decoder pipeline. For this reason, the CU sizes that can use ISP is restricted to a maximum of 64×64. All sub-partitions fulfil the condition of having at least 16 samples. Matrix weighted Intra Prediction (MIP) Matrix weighted intra prediction (MIP) method is a newly added intra prediction technique into VVC. For predicting the samples of a rectangular block of width W and height H, matrix weighted intra prediction (MIP) takes one line of H reconstructed neighbouring boundary samples left of the block and one line of W reconstructed neighbouring boundary samples above the block as input. If the reconstructed samples are unavailable, they are generated as it is done in the conventional intra prediction. The generation of the prediction signal is based on the following three steps, which are averaging, matrix vector multiplication and linear interpolation as shown in Figure 7. Inter prediction in VVC Merge list may include the following candidate(s) 1) Spatial MVP from spatial neighbour CUs2) Temporal MVP from collocated CUs3) History-based MVP from a FIFO table4) Pairwise average MVP (using the candidates already in the list)5) Zero MVs.Merged mode width motion vector difference (MMVD) is to signal MVDs and a resolution index after signaling merge candidate. In Symmetric MVD, motion information of list-1 is derived from motion information of list-0 in bi-prediction case. In Affine prediction, several motion vectors are indicated / signaled for different corners of a block, which are used to derive the motion vectors of sub-block. In affine merge, affine motion information of a block is generated based on the normal or affine motion information of the neighboring blocks. In Sub-block-based temporal motion vector prediction, motion vectors of sub-blocks of the current block are predicted from a proper subblocks in the reference frame which are indicated by the motion vector of a spatial neighboring block (if available). In Adaptive motion vector resolution (AMVR), precision of MVD is signaled for each CU. In Bi-prediction with CU-level weight, an index indicated the weight values for weighted average of two prediction block. Bi-directional optical flow (BDOF) refines the motion vectors in bi-prediction case. BDOF generates two prediction blocks using the signaled motion vectors. Then a motion refinement is calculated two minimize the error between two prediction blocks using their gradient values. The final prediction blocks are refined using the motion refinement and gradient values. Bi-prediction with CU-level weight (BCW) and weighted prediction (WP) In HEVC, the bi-prediction signal is generated by averaging two prediction signals obtained from two different reference pictures and / or using two different motion vectors. In VVC, the bi-prediction mode is extended beyond simple averaging to allow weighted averaging of the two prediction signals. ^bi-pred = ^(8 − ^) ∗ ^^ + ^ ∗ ^^ + 4^ ≫ 3Five weights are allowed in the weighted averaging bi-prediction, w∈{-2,3,4,5,10}. For each bi-predicted CU, the weight w is determined in one of two ways: 1) for a non-merge CU, the weight index is signalled after the motion vector difference; 2) for a merge CU, the weight index is inferred from neighbouring blocks based on the merge candidate index. BCW is only applied to CUs with 256 or more luma samples (i.e., CU width times CU height is greater than or equal to 256). For low-delay pictures, all 5 weights are used. For non-low-delay pictures, only 3 weights (w∈{3,4,5}) are used. -At the encoder, fast search algorithms are applied to find the weight index withoutsignificantly increasing the encoder complexity. These algorithms are summarized as follows. For further details readers are referred to the VTM software and document JVET-L0646. When combined with AMVR, unequal weights are only conditionally checked for 1-pel and 4-pel motion vector precisions if the current picture is a low-delay picture. -When combined with affine, affine ME will be performed for unequal weights if and onlyif the affine mode is selected as the current best mode. -When the two reference pictures in bi-prediction are the same, unequal weights are onlyconditionally checked. -Unequal weights are not searched when certain conditions are met, depending on thePOC distance between current picture and its reference pictures, the coding QP, and the temporal level. The BCW weight index is coded using one context coded bin followed by bypass coded bins. The first context coded bin indicates if equal weight is used; and if unequal weight is used, additional bins are signalled using bypass coding to indicate which unequal weight is used. Weighted prediction (WP) is a coding tool supported by the H.264 / AVC and HEVC standards to efficiently code video content with fading. Support for WP was also added into the VVC standard. WP allows weighting parameters (weight and offset) to be signalled for each reference picture in each of the reference picture lists L0 and L1. Then, during motion compensation, the weight(s) and offset(s) of the corresponding reference picture(s) are applied. WP and BCW are designed for different types of video content. In order to avoid interactions between WP and BCW, which will complicate VVC decoder design, if a CU uses WP, then the BCW weight index is not signalled, and w is inferred to be 4 (i.e. equal weight is applied). For a merge CU, the weight index is inferred from neighbouring blocks based on the merge candidate index. This can be applied to both normal merge mode and inherited affine merge mode. For constructed affine merge mode, the affine motion information is constructed based on the motion information of up to 3 blocks. The BCW index for a CU using the constructed affine merge mode is simply set equal to the BCW index of the first control point MV. In VVC, CIIP and BCW cannot be jointly applied for a CU. When a CU is coded with CIIP mode, the BCW index of the current CU is set to 2, e.g. equal weight. Combined inter and intra prediction (CIIP) In VVC, when a CU is coded in merge mode, if the CU contains at least 64 luma samples (that is, CU width times CU height is equal to or larger than 64), and if both CU width and CU height are less than 128 luma samples, an additional flag is signaled to indicate if the combined inter / intra prediction (CIIP) mode is applied to the current CU. As its name indicates, the CIIP prediction combines an inter prediction signal with an intra prediction signal. The inter prediction signal in the CIIP mode ^^^^^^is derived using the same inter prediction process applied to regular merge mode; and the intra prediction signal ^^^^^^is derived following the regular intra prediction process with the planar mode. Then, the intra and inter prediction signals are combined using weighted averaging, where the weight value is calculated depending on thecoding modes of the top and left neighbouring blocks (depicted in Figure 8) as follows:- If the top neighbor is available and intra coded, then set isIntraTop to 1, otherwise setisIntraTop to 0; -If the left neighbor is available and intra coded, then set isIntraLeft to 1, otherwise setisIntraLeft to 0; -If (isIntraLeft + isIntraTop) is equal to 2, then wt is set to 3;- Otherwise, if (isIntraLeft + isIntraTop) is equal to 1, then wt is set to 2;- Otherwise, set wt to 1.The CIIP prediction is formed as follows: ^CIIP = ^(4 − ^^) ∗ ^^^^^^ + ^^ ∗ ^^^^^^ + 2^ ≫ 2Local illumination compensation (LIC) LIC is an inter prediction technique to model local illumination variation between current block and its prediction block as a function of that between current block template and reference block template. The parameters of the function can be denoted by a scale α and an offset β, which forms a linear equation, that is, α*p[x]+β to compensate illumination changes, where p[x] is a reference sample pointed to by MV at a location x on reference picture. Since α and β can be derived based on current block template and reference block template, no signaling overhead is required for them, except that an LIC flag is signaled for AMVP mode to indicate the use of LIC. The local illumination compensation proposed in JVET-O0066 is used in ECM for uni-prediction inter CUs with the following modifications. • Intra neighbor samples can be used in LIC parameter derivation; • LIC is disabled for blocks with less than 32 luma samples; • For both non-subblock and affine modes, LIC parameter derivation is performed based on the template block samples corresponding to the current CU, instead of partial template block samples corresponding to first top-left 16x16 unit; • Samples of the reference block template are generated by using MC with the block MV without rounding it to integer-pel precision. Handling of out-of-boundary samples (OOB) In bi-directional motion compensation the out of boundary (OOB) prediction samples are discarded and only the non-OOB predictors, when available, are used to generate the final predictor. Specifically, let ^^^_^ and ^^^_^ denote the position of one prediction sample in^,^ ^,^one current block, ^^_^^^,^^and ^^_^^^,^^(x = 0,1) denote the MV of the current block; and ^^^^^^^^^^^^^ are the positions of four boundariesof the picture. One prediction sample is regarded as OOB when at least one of the following conditions is satisfied: (^^^_^^,^ + ^^_^^^,^^) > (^^^^^^^^^^^^+half_pixel), (^^^_^ + ^^_^^^^,^ ^,^) < (^^^^^^^^^^^- half_pixel),(^^^_^^,^ + ^^_^^^,^^) > (^^^^^^^^^^^^^+ half_pixel), (^^^_^^ + ^^_^^^,^ ^,^ ) < (^^^^^^^^^^- half_pixel)where half_pixel is equal to 8 that represents the half-pel sample distance in the 1 / 16-pel sampleprecision. After examining the OOB condition for each sample, the final prediction samples of one bi-directional block are generated as follows: ^^ ^^If ^ is OOB and ^ is non-OOB^,^ ^,^^^^^^ ^^= ^^^,^^,^^^ ^^else if ^ is non-OOB and ^ is OOB^,^ ^,^^^^^^^^= ^^^,^^,^else OOB checking process is also applicable when BCW is enabled. It is noted that this sample-adaptive bi-prediction process only applies to prediction units for which at least a reference bock is first detected as partially or entirely out-of-bounds.Thus, a block-level OOB criteria is first checked. If both prediction blocks are non-OOB, thenthe usual bi-prediction takes place. In-loop filters There are totally three in-loop filters in VVC. Besides a deblocking filter and a SAO(the two loop filters in HEVC), adaptive loop filters (ALF) are applied. The ALF comprises lumaALF, chroma ALF and cross-component ALF (CC-ALF). The ALF filtering process is designed so that luma ALF, chroma ALF and CC-ALF can be executed in parallel. The order of the filtering process in the VVC is the deblocking filter, the SAO and the ALF. The SAO in VVC is the same as that in HEVC. In VVC, an Adaptive Loop Filter (ALF) with block-based filter adaption is applied. For the luma component, one among 25 filters is selected for each 4×4 block, based on the direction and activity of local gradients. Figure 9 shows examples of two diamond filter shapes, which are used in VVC. The7×7 diamond shape is applied for luma component and the 5×5 diamond shape is applied for chroma components. A classification index C for each 4x4 luma component block is derived based on itsdirectionality ^ and a quantized value of activity ^^, as follows:To calculate ^ and ^^, gradients of the horizontal, vertical and two diagonal directionare first calculated using 1-D Laplacian:

[0002] where indices ^ and ^ refer to the coordinates of the upper left sample within the 4 × 4 block and^(^, ^) indicates a reconstructed sample at coordinate To reduce the complexity of block classification, the subsampled 1-D Laplacian calculation is applied. As shown in Figure 10, the same subsampled positions are used for gradient calculation of all directions. Then ^ 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 ^, these values are compared against each other and with two thresholds ^^and ^^: Step 1. If both are true, ^ is set to 0.Step 2. If ^^^^⁄ ^^^^,^^^,^ > ^^^^⁄ ^^^^^,^^^^^,^^ , continue from Step 3; otherwise continue fromStep 4. Step 3. set to 2; otherwise ^ is set toStep 4. otherwise ^ is set toThe activity value ^ is calculated as: ^is further quantized to the range of 0 to 4, inclusively, and the quantized value isdenoted as ^^. For chroma components in a picture, no classification method is applied. 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: ^^(^, ^) = ^(^, ^), ^^(^, ^) = ^(^, ^),Vertical flip: ^^(^, ^) = ^(^, ^ − ^ − 1), ^^(^, ^) = ^(^, ^ − ^ − 1)Rotation: ^^(^, ^) = ^(^ − ^ − 1, ^), ^^(^, ^) = ^(^ − ^ − 1, ^)where ^ is the size of the filter and 0 ≤ ^, ^ ≤ ^ − 1 are coefficients coordinates, such thatlocation (0,0) is at the upper left corner and location (^ − 1, ^ − 1) is at the lower right corner.The transformations are applied to the filter coefficients f (k, l) and to the clippingvalues ^(^, ^) depending on gradient values calculated for that block. The relationship betweenthe transformation and the four gradients of the four directions are summarized in the following table. Gradient values Transformationgd2 < gd1 and gh < gv No transformationgd2 < gd1 and gv < gh Diagonalgd1 < gd2 and gh < gv Vertical flipgd1 < gd2 and gv < gh RotationTable: Mapping of the gradient calculated for one block and the transformations 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 andc(k,l) denotes the decoded clipping parameters. The variable k and l vary between -L / 2 and L / 2where L denotes the filter length. The clipping function ^(^, ^) = min(^, max(−^, ^)), which corresponds to thefunction Clip3 (-y,y,x). The clipping operation introduces non-linearity to make ALF more efficient by reducing the impact of neighbor sample values that are too different with the current sample value. 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. Figure 11 provides a system level diagram of the CC-ALF process withrespect to the SAO, luma ALF and chroma ALF processes. The ALF pipeline therein comprisesapplying luma ALF to the reconstructed luma samples and applying chroma ALF to the reconstructed chroma samples. The reconstructed luma samples are further used as an input to CC-ALF to obtain a chroma correction, which is then added to the output of the chroma ALF. Filtering in CC-ALF is accomplished by applying a linear, diamond shaped filter tothe luma channel. One filter is used for each chroma channel, and the operation is expressed as where (^, ^) is chroma component i location being refined (^^, ^^) is the luma location basedon (^, ^), ^^ is filter support area in luma component, ^^(^^, ^^) represents the filter coefficients.Thus, 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 (MSE) of each chroma channels with respect to the original chroma content. To achieve this, the VTM 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. Thus, the ALFs perform luma and chroma filtering in parallel fashion to lower the mean square error (MSE) between the reconstruction and the original samples. I.e., in VVC the ALF first filters both luma and chroma in parallel, and subsequently also applies cross- component filtering (CC-ALF) to further improve the chroma. Only the luma samples are used as input to the CC-ALF in VVC. The chroma ALF uses chroma reconstruction buffer. However, using luma samples only as an input to CC-ALF and / or chroma reconstruction buffers for refining the chroma components may not be optimal all cases. This is especially true if the correlation between the luma component and the chroma components of the sample is smaller than in a typical situation. Now an improved method for chroma filtering is introduced. A method according to an aspect is shown in Figure 12, where the method comprisesobtaining (1200) a first set of reconstructed samples of a first color channel of an image;obtaining (1202) a second set of reconstructed samples of a second color channel of the image;applying (1204) a first adaptive in-loop filter for the first set of reconstructed samples; applying(1206) a second adaptive in-loop filter for the second set of reconstructed samples; providing(1208) the first set of reconstructed samples and the second set of reconstructed samples as input to a convolutional cross-component model filter; applying (1210) the convolutional cross- component model (CCCM) filter to the first and second set of reconstructed samples to obtain anadditional input for reconstructing the second set of samples; applying (1212) a cross-componentadaptive in-loop filter for outputs of the first adaptive in-loop filter and the second adaptive in-loop filter; and providing (1214) an output of the cross-component adaptive in-loop filter to theoutput of the second adaptive in-loop filter as an additional correction for the second set of samples. According to an embodiment, the first set of reconstructed samples of the first color channel comprise luma components, and the second set of reconstructed samples of the second color channel comprise chroma components. Thus, in the method, an additional filtering stage, CCCM updated chroma buffers, isused as an additional input to chroma ALF and / or to CC-ALF. Therein, a convolutional cross-component model (CCCM) filter is derived and the first set of reconstructed samples, such asluma samples reconstructed by SAO filtering, and the second set of reconstructed samples, suchas chroma samples reconstructed by SAO filtering, are provided as an input to the CCCM filter.The CCCM filter is then applied, using filter coefficients derived for the sets of samples, to the first and second set of reconstructed samples to obtain an additional input for reconstructing thesecond set of samples, such as the chroma samples. This filtering stage may be referred to asCCCM updated chroma buffers. As a result, since not only luma samples are used an input to the cross-component filtering (CC-ALF), but also chroma samples are used, the error against the original luma and chroma samples is further minimized. According to an embodiment, the additional input is provided to the second adaptive in-loop filter. According to an embodiment, the method further comprises performing, by said convolutional cross-component model filter, CCCM filter derivation for obtaining filter coefficients for the samples; and applying CCCM filtering using the filter coefficients. Thus, the additional input obtained from the CCCM filter is provided to the secondALF, such as the chroma ALF. This is illustrated in an exemplified filtering pipeline shown in Figure 13. Therein, an additional filtering stage is inserted between the ALF luma (1306) andALF chroma stages (1312). In the CCCM filter derivation stage (1308), CCCM filter coefficientsare derived at high spatial granularity using the SAO reconstructed luma and chroma as reference samples. According to an embodiment, the method comprises providing an output of the first adaptive in-loop filter as an input to the CCCM filtering. In the CCCM filtering stage (1310), the CCCM filters with the derived filtercoefficients are applied to the luma reconstructed by the first adaptive in-loop filter, i.e. the ALFluma (1306).It is noted that the output of ALF luma has a higher reconstruction quality than theoutput of SAO luma (1300) used as input in the CCCM filter derivation, as well as in the CC-ALF process of Figure 11. When the higher quality luma is used as input in the CCCM filters, ahigher quality version of the chroma may be obtained as an output. The CCCM filtering retains the color space characteristics (obtained in the CCCM filter derivation stage) but converts luminance corrections (such as corrected edges / gradients or smoothened / sharpened textures) intoa higher quality version of the chroma. This higher quality version of the chroma is thenprovided as the additional input is provided to the second adaptive in-loop filter, i.e. the ALFchroma, together with the SAO reconstructed chroma samples (1302, 1304).The output of the second adaptive in-loop filter, i.e. the ALF chroma (1312), is thefurther provided to the cross-component adaptive in-loop chroma filters (CC-ALF Cb, 1314; CC-ALF Cr, 1316) together with the output of the first adaptive in-loop filter, i.e. ALF luma. and thesecond adaptive in-loop filter. The outputs of the cross-component adaptive in-loop chromafilters (CC-ALF Cb, CC-ALF Cr) are then added to the outputs of the second adaptive in-loopfilter (i.e. Cb, Cr) as an additional correction for the chroma samples.According to an embodiment, the additional input is provided to the cross-component adaptive in-loop filter.Thus, the additional input obtained from the CCCM filter is provided to the cross-component adaptive in-loop filter, such as the CC-ALF Cb and CC-ALF Cr. This is illustrated inan exemplified filtering pipeline shown in Figure 14, where the same reference numbering as inFigure 13 is used. Therein, instead of, or additionally to, providing the additional input obtainedfrom the CCCM filter (1310) to the second ALF, such as the chroma ALF (1312), the additionalinput obtained from the CCCM filter (1310) is provided directly to the cross-component adaptivein-loop filter, such as the CC-ALF Cb (1314) and CC-ALF Cr (1316). Therein, the output of thesecond adaptive in-loop filter, i.e. the ALF chroma (1312), together with the output of the firstadaptive in-loop filter, i.e. ALF luma (1306) are all used as inputs for the CC-ALF Cb and CC-ALF Cr. The outputs of the cross-component adaptive in-loop chroma filters (CC-ALF Cb, CC-ALF Cr) are then added to the outputs of the second adaptive in-loop filter (i.e. Cb, Cr) as anadditional correction for the chroma samples, similarly to the embodiment shown in Figure 13.According to an embodiment, the method comprises providing additional filtercoefficients and clipping values for the second adaptive in-loop filter and / or the cross-componentadaptive in-loop filter, wherein said additional filter coefficients and clipping values are derived from neighboring samples of the current input sample. Thus, extra filter coefficients and clipping values are derived from collocated CCCMupdated chroma buffer neighborhood. The filter support area may be defined in various manners,nevertheless being originated from neighboring samples of the current input sample. According to an embodiment, said additional filter coefficients and clipping values are derived using a 3x3 diamond shape filter. For example, a linear, diamond shaped filter as shown in Figure 15 may be applied to the luma channel. 3x3 diamond shape symmetric filter can be chosen to derive 3 new filtercoefficients and clipping values. It is, however, noted that suitable filters may comprise varioussizes and shapes, for example being subject to desired filtering granularity, as described further below. The improved ALF pipeline as provided herein enables to improve the granularity atwhich CCCM model derivation and filtering happens. The CCCM models are derived and applied for small blocks that can be independent of coding and prediction partitions. For example, the said blocks can be 1x1, 2x2, 4x4, etc., and can have square or rectangular shapes. The blocks can also be overlapped or distinct. Compared to the CTU-level CC-ALF filters, as inthe example of Figure 10, the proposed method can track cross-component model at high spatialprecision and therefore also maps finely detailed luma improvements into chroma improvements. This is contrary to the CC-ALF in which the filter coefficients are changed only at CTU level and only 8 different filters are available per picture. With CCCM there can be thousands of filters, for example one for each 8x8 block, without any additional signalling cost. However, the CC-ALF can still be applied and still provides a benefit since the CC- ALF filters are derived at the encoder by minimizing squared error against the original samples. In the filtering stage, the CCCM model performance can be considered. During modelderivation the MSE of the model is obtained and if the said MSE is considered too high, theCCCM stage can be skipped for the given block. It should be understood that all mentioned CCCM stages can be, if necessary, replaced with any cross-component prediction tool such as CCLM, GL-CCCM or any other cross- component prediction tool. For clarity, in the following embodiments the cross-component prediction tool CCCM is used an example. In an embodiment, the CCCM model derivation and filtering can be performed at anygiven granularity for example at 1x1, 2x2, 4x4, 8x8, 16x16, etc., blocks or using rectangular blocks such as 4x8 or 8x4. In an embodiment’ the blocks at which CCCM models are derived and applied can bedistinct or overlapping. In an embodiment, the CCCM blocks can be independent or dependent on the coding or prediction partitioning. For example, instead of using very fine granularity the blocks can follow the chroma or luma partitioning at some precision to accelerate the model derivation and filtering. In an embodiment, during the CCCM model derivation with the MSE, the model canbe examined at every block and if the MSE exceeds a given threshold the CCCM stage can be skipped for the given block. In an embodiment, the MSE threshold can be fixed or signalled from encoder todecoder. In an embodiment, the MSE threshold can be inferred based on underlying coding partitioning, luma sample values or chroma sample values. In an embodiment, the CCCM model can have any number of filter coefficients.In an embodiment, the CCCM model derivation and filtering can be replaced withsimplified variants such as CCLM. In an embodiment, the CCCM model derivation and filtering can be replaced withmore advanced variants such as those considering the gradient and location information (such as GL-CCCM). In an embodiment, the CCCM model derivation stage can be placed before or after theSAO stages. In an embodiment, the CCCM model derivation stage can be placed at any pointbefore the luma ALF stage. In an embodiment, the luma input to the CC-ALF stages can be the input to the ALFluma stage or the output of the ALF luma stage. In an embodiment, the filter may consist of auxiliary information in order to guide the filter in such a way that it improves areas or samples with certain characteristics better. Examples of such auxiliary information are as below: -Input to the filter may include residual information from the luma block;- Input to the filter may include prediction information of the luma block;- Input to the filter may include one or more of the transform coefficients of the lumablock; -Input to the filter may include inputs and / or outputs of the earlier filtering operations. Forexample, input and / or output of deblocking filter, input and / or output of SAO filter, input and / or output of ALF filter; -Input to the filter may include the difference of the inputs and outputs of the earlierfiltering operations. For example, difference of input and output of deblocking filter, difference of input and output of SAO filter, difference of input and output of ALF filter. A scaling operation may be also applied to the difference values before feeding them to the CCCM filter. In an embodiment, the usage of the CCCM stage can be signalled from encoder todecoder. In an embodiment, the usage of the filter may be signalled in different granularities, for example the signalling may be done per each filtering unit such as 1x1, 2x2, etc. Alternatively, the signalling may be done in different granularity than filtering granularity. For example, the activation of the filter may be done in coarser granularity, for each per CTU, and when the filtering mode is enabled for that CTU, the filtering may be done in finer granularity(e.g., 1x1, 2x2, 4x4, …). In this case, in the encoder side, the decision whether to use the filter ornot may be done for the whole CTU based on rate-distortion optimization. In an embodiment, different types and / or sizes of the filter such as conventional CCCM, GL-CCCM, CCLM or any other variant may be decided for each CTU, slice, sub- picture, picture, or sequence level and signalled accordingly. In an embodiment, the CCCM stage can be applied to all chroma components or to aspecified set of chroma components. In an embodiment, the proposed ALF pipeline can be used in any color space.In an embodiment, an additional chroma-to-chroma CCCM stage can be insertedbetween the ALF Cb and ALF Cr stages therefore making the chroma ALF also sequential. In an embodiment, the CCCM model derivation and filtering stage can use downsampled and / or original luma samples. In an embodiment, filtering units may consist of non-overlapping blocks. In this case, the filter derivation process for all filtering units may be done in parallel. In addition, once parameters of certain unit are derived, then the CCCM filtering may begin without too much latency in the pipeline. An apparatus according to an aspect comprises means for obtaining a first set ofreconstructed samples of a first color channel of an image; means for obtaining a second set ofreconstructed samples of a second color channel of the image; means for applying a firstadaptive in-loop filter for the first set of reconstructed samples; means for applying a secondadaptive in-loop filter for the second set of reconstructed samples; means for providing the firstset of reconstructed samples and the second set of reconstructed samples as input to a convolutional cross-component model filter; means for applying the convolutional cross- component model (CCCM) filter to the first and second set of reconstructed samples to obtain anadditional input for reconstructing the second set of samples; means for applying a cross-component adaptive in-loop filter for outputs of the first adaptive in-loop filter and the secondadaptive in-loop filter; and means for providing an output of the cross-component adaptive in-loop filter to the output of the second adaptive in-loop filter as an additional correction for the second set of samples.According to an embodiment, the apparatus comprises means for providing theadditional input to the second adaptive in-loop filter. According to an embodiment, the apparatus comprises means for providing theadditional input to the cross-component adaptive in-loop filter. According to an embodiment, the apparatus comprises means for performing, by saidconvolutional cross-component model filter, CCCM filter derivation for obtaining filtercoefficients for the samples; and means for applying CCCM filtering using the filter coefficients.According to an embodiment, the apparatus comprises means for providing an outputof the first adaptive in-loop filter as an input to the CCCM filtering. According to an embodiment, the apparatus comprises means for providing an outputof the first adaptive in-loop filter as an input to the cross-component adaptive in-loop filter. According to an embodiment, the apparatus comprises means for providing additionalfilter coefficients and clipping values for the second adaptive in-loop filter and / or the cross- component adaptive in-loop filter, wherein said additional filter coefficients and clipping values are derived from neighboring samples of the current input sample. According to an embodiment, the apparatus comprises means for deriving saidadditional filter coefficients and clipping values using a 3x3 diamond shape filter. According to an embodiment, the first set of reconstructed samples of the first color channel comprise luma components, and the second set of reconstructed samples of the second color channel comprise chroma components. As a further aspect, there is provided an apparatus comprising: at least one processor and at least one memory, said at least one memory stored with code thereon, which whenexecuted by said at least one processor, causes the apparatus to perform at least: obtain a first setof reconstructed samples of a first color channel of an image; obtain a second set ofreconstructed samples of a second color channel of the image; apply a first adaptive in-loop filterfor the first set of reconstructed samples; apply a second adaptive in-loop filter for the second setof reconstructed samples; provide the first set of reconstructed samples and the second set ofreconstructed samples as input to a convolutional cross-component model filter; apply the convolutional cross-component model (CCCM) filter to the first and second set of reconstructedsamples to obtain an additional input for reconstructing the second set of samples; apply a cross-component adaptive in-loop filter for outputs of the first adaptive in-loop filter and the secondadaptive in-loop filter; and provide an output of the cross-component adaptive in-loop filter tothe output of the second adaptive in-loop filter as an additional correction for the second set of samples. According to an embodiment, the apparatus comprises code causing the apparatus toprovide the additional input to the second adaptive in-loop filter.According to an embodiment, the apparatus comprises code causing the apparatus toprovide the additional input to the cross-component adaptive in-loop filter.According to an embodiment, the apparatus comprises code causing the apparatus toperform, by said convolutional cross-component model filter, CCCM filter derivation forobtaining filter coefficients for the samples; and apply CCCM filtering using the filtercoefficients. According to an embodiment, the apparatus comprises code causing the apparatus toprovide an output of the first adaptive in-loop filter as an input to the CCCM filtering.According to an embodiment, the apparatus comprises code causing the apparatus toprovide an output of the first adaptive in-loop filter as an input to the cross-component adaptivein-loop filter. According to an embodiment, the apparatus comprises code causing the apparatus toprovide additional filter coefficients and clipping values for the second adaptive in-loop filterand / or the cross-component adaptive in-loop filter, wherein said additional filter coefficients and clipping values are derived from neighboring samples of the current input sample. According to an embodiment, the apparatus comprises code causing the apparatus toderive said additional filter coefficients and clipping values using a 3x3 diamond shape filter.According to an embodiment, the first set of reconstructed samples of the first color channel comprise luma components, and the second set of reconstructed samples of the second color channel comprise chroma components. Such apparatuses may comprise e.g. all or a subset of the functional units disclosed inany of the appended Figures 1a, 1b, 13 – 14 and 16 – 19 for implementing the embodiments.Such an apparatus further comprises code, stored in said at least one memory, which when executed by said at least one processor, causes the apparatus to perform one or more of the embodiments disclosed herein.Figure 16 shows a schematic block diagram of an exemplary apparatus or electronicdevice 50, which may incorporate a codec according to an embodiment of the invention. Figure17 shows a layout of an apparatus according to an example embodiment.The electronic device 50 may for example be a mobile terminal or user equipment of a wireless communication system. However, it would be appreciated that embodiments of the invention may be implemented within any electronic device or apparatus which may require encoding and decoding or encoding or decoding video images. The apparatus 50 may comprise a housing 30 for incorporating and protecting the device. The apparatus 50 further may comprise a display 32 in the form of a liquid crystal display. In other embodiments of the invention the display may be any suitable display technology suitable to display an image or video. The apparatus 50 may further comprise a keypad 34. In other embodiments of the invention any suitable data or user interface mechanismmay be employed. For example, the user interface may be implemented as a virtual keyboard ordata entry system as part of a touch-sensitive display. The apparatus may comprise a microphone 36 or any suitable audio input which may be a digital or analogue signal input. The apparatus 50 may further comprise an audio output device which in embodiments of the invention may be any one of: an earpiece 38, speaker, or an analogue audio or digital audio output connection. The apparatus 50 may also comprise a battery (or in other embodiments of the invention the device may be powered by any suitable mobile energy device such as solar cell, fuel cell or clockwork generator). The apparatus may further comprise a camera capable of recording or capturing images and / or video. The apparatus 50 may further comprise an infrared port for short range line of sight communication to other devices. In other embodiments the apparatus 50 may further comprise any suitable short range communication solution such as for example a Bluetooth wireless connection or a USB / firewire wired connection. The apparatus 50 may comprise a controller 56, processor or processor circuitry forcontrolling the apparatus 50. The controller 56 may be connected to memory 58 which in embodiments of the invention may store both data in the form of image and audio data and / or may also store instructions for implementation on the controller 56. The controller 56 may further be connected to codec circuitry 54 suitable for carrying out coding and decoding of audio and / or video data or assisting in coding and decoding carried out by the controller. The apparatus 50 may further comprise a card reader 48 and a smart card 46, for example a UICC and UICC reader for providing user information and being suitable for providing authentication information for authentication and authorization of the user at a network. The apparatus 50 may comprise radio interface circuitry 52 connected to the controller and suitable for generating wireless communication signals for example for communication with a cellular communications network, a wireless communications system or a wireless local area network. The apparatus 50 may further comprise an antenna 44 connected to the radio interface circuitry 52 for transmitting radio frequency signals generated at the radio interface circuitry 52 to other apparatus(es) and for receiving radio frequency signals from other apparatus(es). The apparatus 50 may comprise a camera capable of recording or detecting individual frames which are then passed to the codec 54 or the controller for processing. The apparatus may receive the video image data for processing from another device prior to transmission and / or storage. The apparatus 50 may also receive either wirelessly or by a wired connection the imagefor coding / decoding. The structural elements of apparatus 50 described above representexamples of means for performing a corresponding function. With respect to Figure 18, an example of a system within which embodiments of the present invention can be utilized is shown. The system 10 comprises multiple communication devices which can communicate through one or more networks. The system 10 may comprise any combination of wired or wireless networks including, but not limited to a wireless cellular telephone network (such as a GSM, UMTS, CDMA network etc.), a wireless local area network (WLAN) such as defined by any of the IEEE 802.x standards, a Bluetooth personal area network, an Ethernet local area network, a token ring local area network, a wide area network, and the Internet. The system 10 may include both wired and wireless communication devices and / or apparatus 50 suitable for implementing embodiments of the invention. For example, the system shown in Figure 18 shows a mobile telephone network 11 anda representation of the internet 28. Connectivity to the internet 28 may include, but is not limited to, long range wireless connections, short range wireless connections, and various wiredconnections including, but not limited to, telephone lines, cable lines, power lines, and similarcommunication pathways. The example communication devices shown in the system 10 may include, but are not limited to, an electronic device or apparatus 50, a combination of a personal digital assistant (PDA) and a mobile telephone 14, a PDA 16, an integrated messaging device (IMD) 18, a desktop computer 20, a notebook computer 22. The apparatus 50 may be stationary or mobile when carried by an individual who is moving. The apparatus 50 may also be located in a mode of transport including, but not limited to, a car, a truck, a taxi, a bus, a train, a boat, an airplane, a bicycle, a motorcycle or any similar suitable mode of transport. The embodiments may also be implemented in a set-top box; i.e. a digital TV receiver, which may / may not have a display or wireless capabilities, in tablets or (laptop) personal computers (PC), which have hardware or software or combination of the encoder / decoder implementations, in various operating systems, and in chipsets, processors, DSPs and / or embedded systems offering hardware / software based coding. Some or further apparatus may send and receive calls and messages and communicate with service providers through a wireless connection 25 to a base station 24. The base station 24 may be connected to a network server 26 that allows communication between the mobile telephone network 11 and the internet 28. The system may include additional communication devices and communication devices of various types. The communication devices may communicate using various transmission technologies including, but not limited to, code division multiple access (CDMA), global systems for mobile communications (GSM), universal mobile telecommunications system (UMTS), time divisional multiple access (TDMA), frequency division multiple access (FDMA), transmission control protocol-internet protocol (TCP-IP), short messaging service (SMS), multimedia messaging service (MMS), email, instant messaging service (IMS), Bluetooth, IEEE 802.11 and any similar wireless communication technology. A communications device involved in implementing various embodiments of the present invention may communicate using various media including, but not limited to, radio, infrared, laser, cable connections, and any suitable connection. Figure 19 is a graphical representation of an example multimedia communicationsystem within which various embodiments may be implemented. A data source 1510 provides a source signal in an analog, uncompressed digital, or compressed digital format, or any combination of these formats. An encoder 1520 may include or be connected with a pre- processing, such as data format conversion and / or filtering of the source signal. The encoder 1520 encodes the source signal into a coded media bitstream. It should be noted that a bitstream to be decoded may be received directly or indirectly from a remote device located within virtually any type of network. Additionally, the bitstream may be received from local hardware or software. The encoder 1520 may be capable of encoding more than one media type, such as audio and video, or more than one encoder 1520 may be required to code different media types of the source signal. The encoder 1520 may also get synthetically produced input, such as graphics and text, or it may be capable of producing coded bitstreams of synthetic media. In the following, only processing of one coded media bitstream of one media type is considered to simplify the description. It should be noted, however, that typically real-time broadcast services comprise several streams (typically at least one audio, video and text sub-titling stream). It should also be noted that the system may include many encoders, but in the figure only oneencoder 1520 is represented to simplify the description without a lack of generality. It should befurther understood that, although text and examples contained herein may specifically describe an encoding process, one skilled in the art would understand that the same concepts and principles also apply to the corresponding decoding process and vice versa. The coded media bitstream may be transferred to a storage 1530. The storage 1530 may comprise any type of mass memory to store the coded media bitstream. The format of the coded media bitstream in the storage 1530 may be an elementary self-contained bitstream format, or one or more coded media bitstreams may be encapsulated into a container file, or the coded media bitstream may be encapsulated into a Segment format suitable for DASH (or a similar streaming system) and stored as a sequence of Segments. If one or more media bitstreamsare encapsulated in a container file, a file generator (not shown in the figure) may be used tostore the one more media bitstreams in the file and create file format metadata, which may also be stored in the file. The encoder 1520 or the storage 1530 may comprise the file generator, or the file generator is operationally attached to either the encoder 1520 or the storage 1530. Some systems operate “live”, i.e. omit storage and transfer coded media bitstream from the encoder 1520 directly to the sender 1540. The coded media bitstream may then be transferred to the sender 1540, also referred to as the server, on a need basis. The format used in the transmission may be an elementary self-contained bitstream format, a packet stream format, a Segment format suitable for DASH (or a similar streaming system), or one or more coded media bitstreams may be encapsulated into a container file. The encoder 1520, the storage 1530, and the server 1540 may reside in the same physical device or they may be included in separate devices. The encoder 1520 and server 1540 may operate with live real-time content, in which case the coded media bitstream is typically not stored permanently, but rather buffered for small periods of time in the content encoder 1520 and / or in the server 1540 to smooth out variations in processing delay, transfer delay, and coded media bitrate. The server 1540 sends the coded media bitstream using a communication protocol stack. The stack may include but is not limited to one or more of Real-Time Transport Protocol (RTP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), Transmission Control Protocol (TCP), and Internet Protocol (IP). When the communication protocol stack is packet-oriented, the server 1540 encapsulates the coded media bitstream into packets. For example, when RTP is used, the server 1540 encapsulates the coded media bitstream into RTP packets according to an RTP payload format. Typically, each media type has a dedicated RTP payload format. It should be again noted that a system may contain more than one server 1540, but for the sake of simplicity, the following description only considers one server 1540. If the media content is encapsulated in a container file for the storage 1530 or for inputting the data to the sender 1540, the sender 1540 may comprise or be operationally attachedto a “sending file parser” (not shown in the figure). In particular, if the container file is nottransmitted as such but at least one of the contained coded media bitstream is encapsulated fortransport over a communication protocol, a sending file parser locates appropriate parts of thecoded media bitstream to be conveyed over the communication protocol. The sending file parser may also help in creating the correct format for the communication protocol, such as packet headers and payloads. The multimedia container file may contain encapsulation instructions, such as hint tracks in the ISOBMFF, for encapsulation of the at least one of the contained media bitstream on the communication protocol. The server 1540 may or may not be connected to a gateway 1550 through a communication network, which may e.g. be a combination of a CDN, the Internet and / or one or more access networks. The gateway may also or alternatively be referred to as a middle-box. For DASH, the gateway may be an edge server (of a CDN) or a web proxy. It is noted that the system may generally comprise any number gateways or alike, but for the sake of simplicity, the following description only considers one gateway 1550. The gateway 1550 may perform different types of functions, such as translation of a packet stream according to one communication protocol stack to another communication protocol stack, merging and forking of data streams, and manipulation of data stream according to the downlink and / or receiver capabilities, such as controlling the bit rate of the forwarded stream according to prevailing downlink network conditions. The gateway 1550 may be a server entity in various embodiments. The system includes one or more receivers 1560, typically capable of receiving, de- modulating, and de-capsulating the transmitted signal into a coded media bitstream. The coded media bitstream may be transferred to a recording storage 1570. The recording storage 1570 may comprise any type of mass memory to store the coded media bitstream. The recording storage 1570 may alternatively or additively comprise computation memory, such as random access memory. The format of the coded media bitstream in the recording storage 1570 may be an elementary self-contained bitstream format, or one or more coded media bitstreams may be encapsulated into a container file. If there are multiple coded media bitstreams, such as an audio stream and a video stream, associated with each other, a container file is typically used and the receiver 1560 comprises or is attached to a container file generator producing a container file from input streams. Some systems operate “live,” i.e. omit the recording storage 1570 and transfer coded media bitstream from the receiver 1560 directly to the decoder 1580. In some systems, only the most recent part of the recorded stream, e.g., the most recent 10-minute excerption of the recorded stream, is maintained in the recording storage 1570, while any earlier recorded data is discarded from the recording storage 1570. The coded media bitstream may be transferred from the recording storage 1570 to the decoder 1580. If there are many coded media bitstreams, such as an audio stream and a video stream, associated with each other and encapsulated into a container file or a single media bitstream is encapsulated in a container file e.g. for easier access, a file parser (not shown in the figure) is used to decapsulate each coded media bitstream from the container file. The recording storage 1570 or a decoder 1580 may comprise the file parser, or the file parser is attached to either recording storage 1570 or the decoder 1580. It should also be noted that the system may include many decoders, but here only one decoder 1580 is discussed to simplify the description without a lack of generality. The coded media bitstream may be processed further by a decoder 1580, whose output is one or more uncompressed media streams. Finally, a renderer 1590 may reproduce the uncompressed media streams with a loudspeaker or a display, for example. The receiver 1560, recording storage 1570, decoder 1580, and renderer 1590 may reside in the same physical device or they may be included in separate devices. A sender 1540 and / or a gateway 1550 may be configured to perform switching between different representations e.g. for switching between different viewports of 360-degree video content, view switching, bitrate adaptation and / or fast start-up, and / or a sender 1540 and / or a gateway 1550 may be configured to select the transmitted representation(s). Switching between different representations may take place for multiple reasons, such as to respond to requests of the receiver 1560 or prevailing conditions, such as throughput, of the network over which the bitstream is conveyed. In other words, the receiver 1560 may initiate switching between representations. A request from the receiver can be, e.g., a request for a Segment or a Subsegment from a different representation than earlier, a request for a change of transmitted scalability layers and / or sub-layers, or a change of a rendering device having different capabilities compared to the previous one. A request for a Segment may be an HTTP GET request. A request for a Subsegment may be an HTTP GET request with a byte range. Additionally or alternatively, bitrate adjustment or bitrate adaptation may be used for example for providing so-called fast start-up in streaming services, where the bitrate of the transmitted stream is lower than the channel bitrate after starting or random-accessing the streaming in order to start playback immediately and to achieve a buffer occupancy level that tolerates occasional packet delays and / or retransmissions. Bitrate adaptation may include multiple representation or layer up-switching and representation or layer down-switching operations taking place in various orders. A decoder 1580 may be configured to perform switching between different representations e.g. for switching between different viewports of 360-degree video content, view switching, bitrate adaptation and / or fast start-up, and / or a decoder 1580 may be configured to select the transmitted representation(s). Switching between different representations may take place for multiple reasons, such as to achieve faster decoding operation or to adapt the transmitted bitstream, e.g. in terms of bitrate, to prevailing conditions, such as throughput, of the network over which the bitstream is conveyed. Faster decoding operation might be needed for example if the device including the decoder 1580 is multi-tasking and uses computing resources for other purposes than decoding the video bitstream. In another example, faster decoding operation might be needed when content is played back at a faster pace than the normal playback speed, e.g. twice or three times faster than conventional real-time playback rate. In the above, some embodiments have been described with reference to and / or usingterminology of HEVC and / or VVC. It needs to be understood that embodiments may besimilarly realized with any video encoder and / or video decoder. In the above, where the example embodiments have been described with reference to an encoder, it needs to be understood that the resulting bitstream and the decoder may have corresponding elements in them. Likewise, where the example embodiments have been described with reference to a decoder, it needs to be understood that the encoder may have structure and / or computer program for generating the bitstream to be decoded by the decoder. The embodiments of the invention described above describe the codec in terms of separate encoder and decoder apparatus in order to assist the understanding of the processes involved. However, it would be appreciated that the apparatus, structures and operations may be implemented as a single encoder-decoder apparatus / structure / operation. Furthermore, it is possible that the coder and decoder may share some or all common elements. Although the above examples describe embodiments of the invention operating within a codec within an electronic device, it would be appreciated that the invention as defined in the claims may be implemented as part of any video codec. Thus, for example, embodiments of the invention may be implemented in a video codec which may implement video coding over fixed or wired communication paths. Thus, user equipment may comprise a video codec such as those described in embodiments of the invention above. It shall be appreciated that the term user equipment is intended to cover any suitable type of wireless user equipment, such as mobile telephones, portable data processing devices or portable web browsers. Furthermore, elements of a public land mobile network (PLMN) may also comprisevideo codecs as described above. In general, the various embodiments of the invention may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, someaspects may be implemented in hardware, while other aspects may be implemented in firmwareor software which may be executed by a controller, microprocessor or other computing device, although the invention is not limited thereto. While various aspects of the invention may be illustrated and described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that these blocks, apparatus, systems, techniques or methods described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof. The embodiments of this invention may be implemented by computer software executable by a data processor of the mobile device, such as in the processor entity, or by hardware, or by a combination of software and hardware. Further in this regard it should be noted that any blocks of the logic flow as in the Figures may represent program steps, or interconnected logic circuits, blocks and functions, or a combination of program steps and logic circuits, blocks and functions. The software may be stored on such physical media as memory chips, or memory blocks implemented within the processor, magnetic media such as hard disk or floppy disks, and optical media such as for example DVD and the data variants thereof, CD. The memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The data processors may be of any type suitable to the local technical environment, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multi-core processor architecture, as non-limiting examples. Embodiments of the inventions may be practiced in various components such as integrated circuit modules. The design of integrated circuits is by and large a highly automated process. Complex and powerful software tools are available for converting a logic level design into a semiconductor circuit design ready to be etched and formed on a semiconductor substrate. Programs, such as those provided by Synopsys, Inc. of Mountain View, California and Cadence Design, of San Jose, California automatically route conductors and locate components on a semiconductor chip using well established rules of design as well as libraries of pre-stored design modules. Once the design for a semiconductor circuit has been completed, the resultant design, in a standardized electronic format (e.g., Opus, GDSII, or the like) may be transmitted toa semiconductor fabrication facility or “fab” for fabrication. The foregoing description has provided by way of exemplary and non-limiting examples a full and informative description of the exemplary embodiment of this invention. However, various modifications and adaptations may become apparent to those skilled in the relevant arts in view of the foregoing description, when read in conjunction with the accompanying drawings and the appended claims. However, all such and similar modifications of the teachings of this invention will still fall within the scope of this invention.

Claims

CLAIMS:

1. An apparatus comprisingmeans for obtaining a first set of reconstructed samples of a first color channel of animage; means for obtaining a second set of reconstructed samples of a second color channelof the image; means for applying a first adaptive in-loop filter for the first set of reconstructedsamples; means for applying a second adaptive in-loop filter for the second set ofreconstructed samples; means for providing the first set of reconstructed samples and the second set ofreconstructed samples as input to a convolutional cross-component model filter; means for applying the convolutional cross-component model (CCCM) filter to thefirst and second set of reconstructed samples to obtain an additional input for reconstructing the second set of samples; means for applying a cross-component adaptive in-loop filter for outputs of the firstadaptive in-loop filter and the second adaptive in-loop filter; and means for providing an output of the cross-component adaptive in-loop filter to theoutput of the second adaptive in-loop filter as an additional correction for the second set of samples.

2. The apparatus according to the claim 1, further comprisingmeans for providing the additional input to the second adaptive in-loop filter.

3. The apparatus according to the claim 1 or 2, further comprisingmeans for providing the additional input to the cross-component adaptive in-loopfilter.

4. The apparatus according to the any preceding claim, further comprisingmeans for performing, by said convolutional cross-component model filter, CCCMfilter derivation for obtaining filter coefficients for the samples; and means for applying CCCM filtering using the filter coefficients.

5. The apparatus according to the claim 4, further comprisingmeans for providing an output of the first adaptive in-loop filter as an input to theCCCM filtering.

6. The apparatus according to any preceding claim, further comprisingmeans for providing an output of the first adaptive in-loop filter as an input to thecross-component adaptive in-loop filter.

7. The apparatus according to any preceding claim, further comprisingmeans for providing additional filter coefficients and clipping values for the secondadaptive in-loop filter and / or the cross-component adaptive in-loop filter, wherein said additionalfilter coefficients and clipping values are derived from neighboring samples of the current input sample.

8. The apparatus according to the claim 7, further comprisingmeans for deriving said additional filter coefficients and clipping values using a 3x3diamond shape filter.

9. The apparatus according to any preceding claim, wherein the first set of reconstructed samplesof the first color channel comprise luma components, and the second set of reconstructed samples of the second color channel comprise chroma components.

10. A method comprising: obtaining a first set of reconstructed samples of a first color channel of an image; obtaining a second set of reconstructed samples of a second color channel of the image; applying a first adaptive in-loop filter for the first set of reconstructed samples;applying a second adaptive in-loop filter for the second set of reconstructed samples; providing the first set of reconstructed samples and the second set of reconstructed samples as input to a convolutional cross-component model filter; applying the convolutional cross-component model (CCCM) filter to the first and second set of reconstructed samples to obtain an additional input for reconstructing the second set of samples; applying a cross-component adaptive in-loop filter for outputs of the first adaptive in-loop filter and the second adaptive in-loop filter; and providing an output of the cross-component adaptive in-loop filter to the output of the second adaptive in-loop filter as an additional correction for the second set of samples.

11. The method according to the claim 10, further comprisingproviding the additional input to the second adaptive in-loop filter.

12. The method according to the claim 10 or 11, further comprisingproviding the additional input to the cross-component adaptive in-loop filter.

13. The method according to the any of claims 10 - 12, further comprisingperforming, by said convolutional cross-component model filter, CCCM filter derivation for obtaining filter coefficients for the samples; and applying CCCM filtering using the filter coefficients.

14. The method according to the claim 13, further comprisingproviding an output of the first adaptive in-loop filter as an input to the CCCM filtering.

15. The method according to any of claims 10 - 14, further comprisingproviding an output of the first adaptive in-loop filter as an input to the cross- component adaptive in-loop filter.

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