Feature-based sample classification for reference filtering

Abstract

A video coder classifies, based on one or more features detected from samples of a reference block for a current block and of a plurality of reference samples neighboring the reference block, each sample of the reference block and of the plurality of reference samples. A plurality of filters is determined based on the classified samples, of the plurality of reference samples, and corresponding samples neighboring the current block. A prediction block is determined by applying the plurality of filters to the classified samples of the reference block. The coder codes the current block based on the prediction block.

Description

Docket No.: 23-2054PCT TITLE Feature-based Sample Classification for Reference Filtering CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application Nos.63 / 616,713, filed December 31, 2023 and 63 / 572,148, filed March 29, 2024, which are hereby incorporated by reference in their entireties. BRIEF DESCRIPTION OF THE DRAWINGS

[0002] Some features are shown by way of example, and not by limitation, in the accompanying drawings. In the drawings, like numerals reference similar elements.

[0003] FIG.1 shows an example video coding / decoding system in which embodiments of the present disclosure may be implemented.

[0004] FIG.2 shows an example encoder in which embodiments of the present disclosure may be implemented.

[0005] FIG.3 shows an example decoder in which embodiments of the present disclosure may be implemented.

[0006] FIG.4 shows an example quadtree partitioning of a coding tree block (CTB).

[0007] FIG.5 shows an example quadtree corresponding to the example quadtree partitioning of the CTB in FIG.4.

[0008] FIG.6 shows examples of binary tree and ternary tree partitions.

[0009] FIG.7 shows an example of combined quadtree and multi-type tree partitioning of a CTB.

[0010] FIG.8 shows an example tree corresponding to the combined quadtree and multi-type tree partitioning of the CTB shown in FIG.7.

[0011] FIG.9 shows an example set of reference samples determined for intra prediction of a current block.

[0012] FIGS.10A and 10B show example intra prediction modes.

[0013] FIG.11 shows an example of a current block and corresponding reference samples.

[0014] FIG.12 shows an example of applying an intra prediction mode (e.g., an angular mode) for prediction of a current block.

[0015] FIG.13A shows an example of inter prediction performed for a current block in a current picture.

[0016] FIG.13B shows an example motion vector.

[0017] FIG.14 shows an example of bi-prediction performed for a current block.

[0018] FIG.15A shows example spatial candidate neighboring blocks relative to a current block being coded.

[0019] FIG.15B shows example locations of two temporal, co-located blocks relative to a current block.

[0020] FIG.16 shows an example of intra block copy (IBC).

[0021] FIG.17A shows an example of a current block and a reference block with corresponding templates used in determining scale and offset parameters for local illumination compensation (LIC) during inter prediction, according to some embodiments.

[0022] FIG.17B shows a process for generating a prediction block when LIC is used during inter prediction, according to some embodiments.Docket No.: 23-2054PCT

[0023] FIG.18A shows a process for generating a prediction block by applying an illumination compensation function (e.g., a filter model) that uses a multiple-tap filter to generate predicted samples from samples of the reference template, according to some embodiments.

[0024] FIG.18B shows an example reference template and example multiple-tap filter models that can be applied to the reference template to generate a multi-tap filter, according to some embodiments.

[0025] FIG.19A shows an example process of using the gradients of multiple-tap filter samples to obtain illumination compensated predicted samples for inter prediction, according to some embodiments.

[0026] FIG.19B shows examples of first-order derivatives and second-order derivatives of example samples for filtering, according to some embodiments.

[0027] FIG.20 shows a flowchart of a process of signaling illumination compensation, according to some embodiments.

[0028] FIG.21 shows a flowchart of a process by which the decoder can determine, when using inter prediction merge mode, whether illumination compensation based on multi-parametric reference filtering (MPRF) is used for the block, according to some embodiments.

[0029] FIG.22 shows an example coding scheme to efficiently encode and decode an indication of filter models (e.g., an MPRF model), according to some embodiments.

[0030] FIG.23A shows a flowchart of a method of deriving a filter model to be applied for illumination compensation in inter prediction, according to some embodiments.

[0031] FIG.23B shows an example reference template format and a current template format that are used to derive the filter model of a plurality of filter models in the method shown in the flowchart of FIG.23A, according to some embodiments.

[0032] FIG.24 shows an example of when filter model parameters can be obtained from a merge candidate, according to some embodiments.

[0033] FIG.25A and FIG.25B show example block sizes of merge candidate blocks that can be considered when deciding whether to obtain filter model parameters from one of the merge candidates, according to some embodiments.

[0034] FIG.26 shows a flowchart of a method for applying illumination compensation based on MPRF in inter prediction, according to some embodiments.

[0035] FIG.27 shows a flowchart of a method for determining a current block that has been encoded by applying illumination compensation based on multi-parametric reference filtering (MPRF) in inter prediction, according to some embodiments.

[0036] FIG.28A is a schematic view of an activity classifier of a coder, according to some embodiments.

[0037] FIG.28B shows an example vertical Laplacian filter.

[0038] FIG.28C shows an example horizontal Laplacian filter.

[0039] FIG.29A is a schematic view of an activity classifier of a coder, according to some embodiments.Docket No.: 23-2054PCT

[0040] FIG.29B shows an example diagonal Laplacian filter (from top-right to bottom-left).

[0041] FIG.29C shows an example diagonal Laplacian filter (from top-left to bottom-right).

[0042] FIG.30 shows a flowchart of an example method for determining a prediction block, according to some embodiments.

[0043] FIG.31 shows a flowchart of an example method for determining a prediction block, according to some embodiments.

[0044] FIG.32 is a schematic view of an activity classifier of a coder, according to some embodiments.

[0045] FIG.33 shows a flowchart of an example method for classifying reference samples associated with a reference block based on detecting, at least from samples of the reference block, one or more feature related to activity, according to some embodiments.

[0046] FIG.34 shows a flowchart of an example method for classifying samples of a reference block based on detecting, at least from samples of the reference block, one or more feature related to directionality of the samples, according to some embodiments.

[0047] FIG.35 is a diagram showing an example of using a plurality of thresholds corresponding to a plurality of edge detection filters to classify samples of a template of a block, according to some embodiments.

[0048] FIG.36A shows an example of determining one or more thresholds using a plurality of directional filters to determine directionalities of samples of a reference block, according to some embodiments.

[0049] FIG.36B shows an example of determining one or more thresholds using a plurality of directional filters to determine directionalities of samples of a current template of current block, according to some embodiments.

[0050] FIG.37 shows a flowchart of an example method for determining values representing directionalities of samples of a reference block based on generating a histogram of gradients (HoG), according to some embodiments.

[0051] FIG.38A shows an example of a horizontal spatial filter.

[0052] FIG.38B shows an example of a vertical spatial filter.

[0053] FIG.39 shows an example of a plurality of spatial filters used to determine a value representing a directionality of a sample on which the plurality of spatial filters is applied, according to some embodiments.

[0054] FIG.40 shows an example of selecting values of subsets of spatial neighboring samples of a sample to classify that sample as being in one of a plurality of groups, according to some embodiments.

[0055] FIG.41 shows a flowchart of an example method for applying feature-based classification to reference block samples and applying multi-parametric filters to the classified samples of the reference block to predict a current block, according to some embodiments.

[0056] FIG.42 illustrates a block diagram of an example computer system in which embodiments of the present disclosure may be implemented. DETAILED DESCRIPTION

[0057] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the disclosure. However, it will be apparent to those skilled in the art that the disclosure, includingDocket No.: 23-2054PCT structures, systems, and methods, may be practiced without these specific details. The description and representation herein are the common means used by those experienced or skilled in the art to most effectively convey the substance of their work to others skilled in the art. In other instances, well-known methods, procedures, components, and circuitry have not been described in detail to avoid unnecessarily obscuring aspects of the disclosure.

[0058] References in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

[0059] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed, but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.

[0060] The term “computer-readable medium” includes, but is not limited to, portable or non-portable storage devices, optical storage devices, and various other mediums capable of storing, containing, or carrying instruction(s) and / or data. A computer-readable medium may include a non-transitory medium in which data can be stored and that does not include carrier waves and / or transitory electronic signals propagating wirelessly or over wired connections. Examples of a non-transitory medium may include, but are not limited to, a magnetic disk or tape, optical storage media such as compact disk (CD) or digital versatile disk (DVD), flash memory, memory or memory devices. A computer-readable medium may have stored thereon code and / or machine-executable instructions that may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and / or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, or the like.

[0061] Furthermore, embodiments may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks (e.g., a computer-program product) may be stored in a computer-readable or machine-readable medium. A processor(s) may perform the necessary tasks.Docket No.: 23-2054PCT

[0062] A video sequence, comprising multiple pictures / frames, may be represented in digital form for storage and / or transmission. Representing a video sequence in digital form may require a large quantity of bits. Large data sizes that may be associated with video sequences may require significant resources for storage and / or transmission. Video encoding may be used to compress a size of a video sequence for more efficient storage and / or transmission. Video decoding may be used to decompress a compressed video sequence for display and / or other forms of consumption.

[0063] FIG.1 shows an example video coding / decoding system 100 in which embodiments of the present disclosure may be implemented. Video coding / decoding system 100 comprises a source device 102, a transmission medium 104, and a destination device 106. Source device 102 encodes a video sequence 108 into a bitstream 110 for more efficient storage and / or transmission. Source device 102 may store and / or send / transmit bitstream 110 to destination device 106 via transmission medium 104. Destination device 106 decodes bitstream 110 to display video sequence 108. Destination device 106 may receive bitstream 110 from source device 102 via transmission medium 104. Source device 102 and / or destination device 106 may be any of a plurality of different devices (e.g., a desktop computer, laptop computer, tablet computer, smart phone, wearable device, television, camera, video gaming console, set-top box, video streaming device, etc.).

[0064] Source device 102 may comprise (e.g., for encoding video sequence 108 into bitstream 110) one or more of a video source 112, an encoder 114, and / or an output interface 116. Video source 112 may provide and / or generate video sequence 108 based on a capture of a natural scene and / or a synthetically generated scene. A synthetically generated scene may be a scene comprising computer generated graphics and / or screen content. Video source 112 may comprise a video capture device (e.g., a video camera), a video archive comprising previously captured natural scenes and / or synthetically generated scenes, a video feed interface to receive captured natural scenes and / or synthetically generated scenes from a video content provider, and / or a processor to generate synthetic scenes.

[0065] A video sequence, such as video sequence 108, may comprise a series of pictures (also referred to as frames). A video sequence may achieve an impression of motion based on successive presentation of pictures of the video sequence using a constant time interval or variable time intervals between the pictures. A picture may comprise one or more sample arrays of intensity values. The intensity values may be taken (e.g., measured, determined, provided) at a series of regularly spaced locations within a picture. A color picture may comprise (e.g., typically comprises) a luminance sample array and two chrominance sample arrays. The luminance sample array may comprise intensity values representing the brightness (e.g., luma component, Y) of a picture. The chrominance sample arrays may comprise intensity values that respectively represent the blue and red components of a picture (e.g., chroma components, Cb and Cr) separate from the brightness. Other color picture sample arrays may be possible based on different color schemes (e.g., a red, green, blue (RGB) color scheme). A pixel, in a color picture, may refer to / comprise / be associated with all intensity values (e.g., luma component, chroma components), for a given location, in the sample arrays (e.g., three sample arrays are used for one luma component and two chroma components, respectively) used to represent color pictures. A monochrome picture may comprise a single, luminanceDocket No.: 23-2054PCT sample array. A pixel, in a monochrome picture, may refer to / comprise / be associated with the intensity value (e.g., luma component) at a given location in the single, luminance sample array used to represent monochrome pictures.

[0066] Encoder 114 may encode video sequence 108 into bitstream 110. Encoder 114 may apply / use (e.g., to encode video sequence 108) one or more prediction techniques to reduce redundant information in video sequence 108. Redundant information is information that may be predicted at a decoder and need not be transmitted to the decoder for accurate decoding of video sequence 108. For example, encoder 114 may apply spatial prediction (e.g., intra-frame or intra prediction), temporal prediction (e.g., inter-frame prediction or inter prediction), inter-layer prediction, and / or other prediction techniques to reduce redundant information in video sequence 108. Encoder 114 may partition pictures comprising video sequence 108 into rectangular regions referred to as blocks, for example, before applying one or more prediction techniques. Encoder 114 may then encode a block using the one or more of the prediction techniques.

[0067] For temporal prediction, encoder 114 may search for a block similar to the block being encoded in another picture (e.g., referred to as a reference picture) of video sequence 108. The block determined during the search (e.g., referred to as a prediction block) may then be used to predict the block being encoded. For spatial prediction, encoder 114 may form a prediction block based on data from reconstructed neighboring samples of the block to be encoded within the same picture of video sequence 108. A reconstructed sample refers to a sample that was encoded and then decoded. Encoder 114 may determine a prediction error (e.g., also referred to as a residual) based on the difference between a block being encoded and a prediction block. The prediction error may represent non-redundant information that may be sent / transmitted to a decoder for accurate decoding of video sequence 108.

[0068] Encoder 114 may apply a transform to the prediction error (e.g. using a discrete cosine transform (DCT), or any other transform) to generate transform coefficients. Encoder 114 may form bitstream 110 based on the transform coefficients and other information used to determine prediction blocks using / based on prediction types, motion vectors, and / or prediction modes. Encoder 114 may perform one or more of quantization and entropy coding of the transform coefficients and / or the other information used to determine the prediction blocks, for example, before forming bitstream 110. The quantization and / or the entropy coding may further reduce the quantity of bits needed to store and / or transmit video sequence 108.

[0069] Output interface 116 may be configured to write and / or store bitstream 110 onto transmission medium 104 for transmission to destination device 106. In addition or alternatively, output interface 116 may be configured to send / transmit, upload, and / or stream bitstream 110 to destination device 106 via transmission medium 104. Output interface 116 may comprise a wired and / or a wireless transmitter configured to send / transmit, upload, and / or stream bitstream 110 in accordance with one or more proprietary, open-source, and / or standardized communication protocols (e.g., Digital Video Broadcasting (DVB) standards, Advanced Television Systems Committee (ATSC) standards, Integrated Services Digital Broadcasting (ISDB) standards, Data Over Cable Service Interface Specification (DOCSIS) standards, 3rd Generation Partnership Project (3GPP) standards, Institute of Electrical andDocket No.: 23-2054PCT Electronics Engineers (IEEE) standards, Internet Protocol (IP) standards, Wireless Application Protocol (WAP) standards, and / or any other communication protocol).

[0070] Transmission medium 104 may comprise wireless, wired, and / or computer readable medium. For example, transmission medium 104 may comprise one or more wires, cables, air interfaces, optical discs, flash memory, and / or magnetic memory. In addition or alternatively, transmission medium 104 may comprise one or more networks (e.g., the internet) or file servers configured to store and / or send / transmit encoded video data.

[0071] Destination device 106 may decode bitstream 110 into video sequence 108 for display. Destination device 106 may comprise one or more of an input interface 118, a decoder 120, and / or a video display 122. Input interface 118 may be configured to read bitstream 110 stored on transmission medium 104 by source device 102. In addition or alternatively, input interface 118 may be configured to receive, download, and / or stream bitstream 110 from source device 102 via transmission medium 104. Input interface 118 may comprise a wired and / or a wireless receiver configured to receive, download, and / or stream bitstream 110 in accordance with one or more proprietary, open- source, standardized communication protocols, and / or any other communication protocol (e.g., such as referenced herein).

[0072] Decoder 120 may decode video sequence 108 from encoded bitstream 110. The decoder 120 may generate prediction blocks for pictures of video sequence 108 in a similar manner as encoder 114 and determine the prediction errors for the blocks, for example, to decode video sequence 108. Decoder 120 may generate the prediction blocks using / based on prediction types, prediction modes, and / or motion vectors received in bitstream 110. Decoder 120 may determine the prediction errors using the transform coefficients received in bitstream 110. Decoder 120 may determine the prediction errors by weighting transform basis functions using the transform coefficients. Decoder 120 may combine the prediction blocks and the prediction errors to decode video sequence 108. Video sequence 108 at the destination device 106 may be, or may not necessarily be, the same video sequence sent, such as video sequence 108 as sent by the source device 102. Decoder 120 may decode a video sequence that approximates video sequence 108, for example, because of lossy compression of video sequence 108 by encoder 114 and / or errors introduced into encoded bitstream 110 during transmission to destination device 106.

[0073] Video display 122 may display video sequence 108 to a user. Video display 122 may comprise a cathode rate tube (CRT) display, a liquid crystal display (LCD), a plasma display, a light emitting diode (LED) display, and / or any other display device suitable for displaying video sequence 108.

[0074] Video coding / decoding system 100 is merely an example and video encoding / decoding systems different from the video coding / decoding system 100 and / or modified versions of the video coding / decoding system 100 may similarly perform the methods and processes as described herein. For example, the video coding / decoding system 100 may comprise other components and / or arrangements. For example, video source 112 may be external to source device 102. Similarly, video display 122 may be external to destination device 106 or omitted altogether (e.g., if video sequence 108 is intended for consumption by a machine and / or storage device). In an example, source device 102 may further comprise a video decoder and destination device 106 may further comprise a video encoder. ForDocket No.: 23-2054PCT example, source device 102 may be configured to further receive an encoded bitstream from destination device 106 to support two-way video transmission between the devices.

[0075] Encoder 114 and / or decoder 120 may operate according to one or more proprietary or industry video coding standards. For example, encoder 114 and / or decoder 120 may operate in accordance with one or more proprietary, open-source, and / or standardized protocols (e.g., International Telecommunications Union Telecommunication Standardization Sector (ITU-T) H.263, ITU-T H.264 and Moving Picture Expert Group (MPEG)-4 Visual (also known as Advanced Video Coding (AVC)), ITU-T H.265 and MPEG-H Part 2 (also known as High Efficiency Video Coding (HEVC)), ITU-T H.265 and MPEG-I Part 3 (also known as Versatile Video Coding (VVC)), the WebM VP8 and VP9 codecs, and / or AOMedia Video 1 (AV1), and / or any other video coding protocol).

[0076] FIG.2 shows an example encoder. Encoder 200 as shown in FIG.2 may implement one or more processes described herein. Encoder 200 may encode a video sequence 202 into a bitstream 204 for more efficient storage and / or transmission. Encoder 200 may be implemented in video coding / decoding system 100 as shown in FIG.1 (e.g., as encoder 114) or in any computing, communication, or electronic device (e.g., desktop computer, laptop computer, tablet computer, smart phone, wearable device, television, camera, video gaming console, set-top box, video streaming device, etc.). Encoder 200 may comprise one or more of an inter prediction unit 206, an intra prediction unit 208, combiners 210 and 212, a transform and quantization unit (TR + Q) 214, an inverse transform and quantization unit (iTR + iQ) 216, an entropy coding unit 218, one or more filters 220, and / or a buffer 222.

[0077] Encoder 200 may partition pictures (e.g., frames) of (e.g., comprising) video sequence 202 into blocks and encode video sequence 202 on a block-by-block basis. Encoder 200 may perform / apply a prediction technique on a block being encoded using either inter prediction unit 206 or intra prediction unit 208. Inter prediction unit 206 may perform inter prediction by searching for a block similar to the block being encoded in another, reconstructed picture (e.g., a reference picture) of video sequence 202. A reconstructed picture refers to a picture that was encoded and then decoded. The block determined during the search (e.g., referred to as a prediction block) may then be used to predict the block being encoded to remove redundant information. Inter prediction unit 206 may exploit temporal redundancy or similarities in scene content from picture to picture in video sequence 202 to determine the prediction block. For example, scene content between pictures of video sequence 202 may be similar except for differences due to motion and / or affine transformation of the screen content over time.

[0078] Intra prediction unit 208 may perform intra prediction by forming a prediction block based on data from reconstructed neighboring samples of the block to be encoded within the same picture of video sequence 202. A reconstructed sample refers to a sample that was encoded and then decoded. Intra prediction unit 208 may exploit spatial redundancy or similarities in scene content within a picture of video sequence 202 to determine the prediction block. For example, the texture of a region of scene content in a picture may be similar to the texture in the immediate surrounding area of the region of the scene content in the same picture.Docket No.: 23-2054PCT

[0079] Combiner 210 may determine a prediction error (e.g., referred to as a residual) based on the difference between the block being encoded and the prediction block. The prediction error may represent non-redundant information that may be sent / transmitted to a decoder for accurate decoding of video sequence 202.

[0080] Transform and quantization unit (TR + Q) 214 may transform and quantize the prediction error. Transform and quantization unit 214 may transform the prediction error into transform coefficients by applying, for example, a DCT to reduce correlated information in the prediction error. Transform and quantization unit 214 may quantize the coefficients by mapping data of the transform coefficients to a predefined set of representative values. Transform and quantization unit 214 may quantize the coefficients to reduce irrelevant information in bitstream 204. The irrelevant information refers to information that may be removed from the coefficients without producing visible and / or perceptible distortion in video sequence 202 after decoding (e.g., at a receiving device).

[0081] Entropy coding unit 218 may apply one or more entropy coding methods to the quantized transform coefficients to further reduce the bit rate. For example, entropy coding unit 218 may apply context adaptive variable length coding (CAVLC), context adaptive binary arithmetic coding (CABAC), and / or syntax-based context-based binary arithmetic coding (SBAC). The entropy coded coefficients may be packed to form bitstream 204.

[0082] Inverse transform and quantization unit (iTR + iQ) 216 may inverse quantize and inverse transform the quantized transform coefficients to determine a reconstructed prediction error. Combiner 212 may combine the reconstructed prediction error with the prediction block to form a reconstructed block. Filter(s) 220 may filter the reconstructed block, for example, using a deblocking filter and / or a sample-adaptive offset (SAO) filter. Buffer 222 may store the reconstructed block for prediction of one or more other blocks in the same and / or different picture of video sequence 202.

[0083] Encoder 200 may further comprise an encoder control unit. The encoder control unit may be configured to control one or more units of encoder 200 as shown in FIG.2. The encoder control unit may control the one or more units of encoder 200 such that bitstream 204 may be generated in conformance with the requirements of one or more proprietary coding protocols, industry video coding standards, and / or any other video cording protocol. For example, the encoder control unit may control the one or more units of encoder 200 such that bitstream 204 may be generated in conformance with one or more of ITU-T H.263, AVC, HEVC, VVC, VP8, VP9, AV1, and / or any other video coding standard / format.

[0084] The encoder control unit may be configured to attempt to minimize (or reduce) the bitrate of bitstream 204 and / or maximize (or increase) the reconstructed video quality (e.g., within the constraints of a proprietary coding protocol, industry video coding standard, and / or any other video cording protocol). For example, the encoder control unit may be configured to attempt to minimize or reduce the bitrate of bitstream 204 such that the reconstructed video quality does not fall below a certain level / threshold, and / or to maximize or increase the reconstructed video quality such that the bitrate of bitstream 204 does not exceed a certain level / threshold. The encoder control unit may determine / control one or more of: partitioning of the pictures of video sequence 202 into blocks, whether a block is inter predicted by inter prediction unit 206 or intra predicted by intra prediction unit 208, a motion vector for interDocket No.: 23-2054PCT prediction of a block, an intra prediction mode among a plurality of intra prediction modes for intra prediction of a block, filtering performed by filter(s) 220, and / or one or more transform types and / or quantization parameters applied by transform and quantization unit 214. The encoder control unit may determine / control one or more of the above based on a rate-distortion measure for a block or picture being encoded. The encoder control unit may determine / control one or more of the above to reduce the rate-distortion measure for a block or picture being encoded.

[0085] The prediction type used to encode a block (intra or inter prediction), prediction information of the block (intra prediction mode if intra predicted, motion vector, etc.), and / or transform and / or quantization parameters, may be sent to entropy coding unit 218 to be further compressed (e.g., to reduce the bitrate). For example, entropy coding unit 218 may apply context adaptive variable length coding (CAVLC), context adaptive binary arithmetic coding (CABAC), and / or syntax-based context-based binary arithmetic coding (SBAC) to achieve further compression. The prediction type, prediction information, and / or transform and / or quantization parameters may be packed with the prediction error to form bitstream 204.

[0086] Encoder 200 is merely an example and encoders different from encoder 200 and / or modified versions of encoder 200 may perform the methods and processes as described herein. For example, encoder 200 may comprise other components and / or arrangements. One or more of the components shown in FIG.2 may be optionally included in encoder 200 (e.g., entropy coding unit 218 and / or filters(s) 220).

[0087] FIG.3 shows an example decoder. A decoder 300 as shown in FIG.3 may implement one or more processes described herein. Decoder 300 may decode a bitstream 302 into a decoded video sequence 304 for display and / or some other form of consumption. Decoder 300 may be implemented in video coding / decoding system 100 in FIG.1 and / or in a computing, communication, or electronic device (e.g., desktop computer, laptop computer, tablet computer, smart phone, wearable device, television, camera, video gaming console, set-top box, and / or video streaming device). Decoder 300 may comprise an entropy decoding unit 306, an inverse transform and quantization (iTR + iQ) unit 308, a combiner 310, one or more filters 312, a buffer 314, an inter prediction unit 316, and / or an intra prediction unit 318.

[0088] Decoder 300 may comprise a decoder control unit configured to control one or more units of decoder 300. The decoder control unit may control the one or more units of decoder 300 such that bitstream 302 is decoded in conformance with the requirements of one or more proprietary coding protocols, industry video coding standards, and / or any other communication protocol. For example, the decoder control unit may control the one or more units of decoder 300 such that the bitstream 302 is decoded in conformance with one or more of ITU-T H.263, AVC, HEVC, VVC, VP8, VP9, AV1, and / or any other video coding standard / format.

[0089] The decoder control unit may determine / control one or more of: whether a block is inter predicted by inter prediction unit 316 or intra predicted by intra prediction unit 318, a motion vector for inter prediction of a block, an intra prediction mode among a plurality of intra prediction modes for intra prediction of a block, filtering performed by filter(s) 312, and / or one or more inverse transform types and / or inverse quantization parameters to be applied byDocket No.: 23-2054PCT inverse transform and quantization unit 308. One or more of the control parameters used by the decoder control unit may be packed in bitstream 302.

[0090] Entropy decoding unit 306 may entropy decode the bitstream 302. For example, entropy decoding unit 306 may apply context adaptive variable length coding (CAVLC), context adaptive binary arithmetic coding (CABAC), and syntax-based context-based binary arithmetic coding (SBAC) to decompress the prediction type used to encode a block (intra or inter prediction), prediction information of the block (intra prediction mode if intra predicted, motion vector, etc.), and transform and quantization parameters. Inverse transform and quantization unit 308 may inverse quantize and / or inverse transform the quantized transform coefficients to determine a decoded prediction error. Combiner 310 may combine the decoded prediction error with a prediction block to form a decoded block. The prediction block may be generated by intra prediction unit 318 or inter prediction unit 316 (e.g., as described above with respect to encoder 200 in FIG 2). Filter(s) 312 may filter the decoded block, for example, using a deblocking filter and / or a sample-adaptive offset (SAO) filter. Buffer 314 may store the decoded block for prediction of one or more other blocks in the same and / or different picture of the video sequence in bitstream 302. Decoded video sequence 304 may be output from filter(s) 312 as shown in FIG.3.

[0091] Decoder 300 is merely an example and decoders different from decoder 300 and / or modified versions of decoder 300 may perform the methods and processes as described herein. For example, decoder 300 may have other components and / or arrangements. One or more of the components shown in FIG.3 may be optionally included in decoder 300 (e.g., entropy decoding unit 306 and / or filters(s) 312).

[0092] Although not shown in FIGS.2 and 3, each of encoder 200 and decoder 300 may further comprise an intra block copy unit in addition to inter prediction and intra prediction units. The intra block copy unit may perform / operate similar to an inter prediction unit but may predict blocks within the same picture. For example, the intra block copy unit may exploit repeated patterns that appear in screen content. The screen content may include computer generated text, graphics, animation, etc.

[0093] Video encoding and / or decoding may be performed on a block-by-block basis. The process of partitioning a picture into blocks may be adaptive based on the content of the picture. For example, larger block partitions may be used in areas of a picture with higher levels of homogeneity to improve coding efficiency.

[0094] A picture (e.g., in HEVC, or any other coding standard / format) may be partitioned into non-overlapping square blocks, which may be referred to as coding tree blocks (CTBs). The CTBs may comprise samples of a sample array. A CTB may have a size of 2nx2n samples, where n may be specified by a parameter of the encoding system. For example, n may be 4, 5, 6, or any other value. A CTB may have any other size. A CTB may be further partitioned by a recursive quadtree partitioning into coding blocks (CBs) of half vertical and half horizontal size. The CTB may form the root of the quadtree. A CB that is not split further as part of the recursive quadtree partitioning may be referred to as a leaf CB of the quadtree, and otherwise may be referred to as a non-leaf CB of the quadtree. A CB may have a minimum size specified by a parameter of the encoding system. For example, a CB may have a minimum size of 4x4, 8x8, 16x16, 32x32, 64x64 samples, or any other minimum size. A CB may be further partitioned into oneDocket No.: 23-2054PCT or more prediction blocks (PBs) for performing inter and / or intra prediction. A PB may be a rectangular block of samples on which the same prediction type / mode may be applied. For transformations, a CB may be partitioned into one or more transform blocks (TBs). A TB may be a rectangular block of samples that may determine / indicate an applied transform size.

[0095] FIG.4 shows an example quadtree partitioning of a CTB 400. FIG.5 shows an example quadtree 500 corresponding to the example quadtree partitioning of CTB 400 in FIG.4. As shown in the examples of FIGS.4 and 5, CTB 400 may first be partitioned into four CBs of half vertical and half horizontal size. Three of the resulting CBs of the first level partitioning of CTB 400 are leaf CBs. The three leaf CBs of the first level partitioning of CTB 400 are respectively labeled 7, 8, and 9 in FIGS.4 and 5. The non-leaf CB of the first level partitioning of CTB 400 is partitioned into four sub-CBs of half vertical and half horizontal size. Three of the resulting sub-CBs of the second level partitioning of CTB 400 are leaf CBs. The three leaf CBs of the second level partitioning of CTB 400 are respectively labeled 0, 5, and 6 in FIGS.4 and 5. Finally, The non-leaf CB of the second level partitioning of CTB 400 is partitioned into four leaf CBs of half vertical and half horizontal size. The four leaf CBs are respectively labeled 1, 2, 3, and 4 in FIGS.4 and 5.

[0096] The example CTB 400 of FIG.4 is partitioned into 10 leaf CBs respectively labeled 0-9, but may be partitioned into other quantities of leaf CBs. The 10 leaf CBs may correspond to 10 CB leaf nodes (e.g., 10 CB leaf nodes of quadtree 500 as shown in FIG.5). In other examples, a CTB may be partitioned into a different number of leaf CBs. The resulting quadtree partitioning of CTB 400 may be scanned using a z-scan (e.g., left-to-right, top-to- bottom) to form the sequence order for encoding / decoding the CB leaf nodes. A numeric label (e.g., indicator, index) of each CB leaf node in FIGS.4 and 5 may correspond to the sequence order for encoding / decoding. For example, CB leaf node 0 may be encoded / decoded first and CB leaf node 9 may be encoded / decoded last. Although not shown in FIGS.4 and 5, each CB leaf node may comprise one or more PBs and / or TBs.

[0097] A picture, in VVC (or in any other coding standard / format), may be partitioned in a similar manner (such as in HEVC). A picture may be first partitioned into non-overlapping square CTBs. The CTBs may then be partitioned, using a recursive quadtree partitioning, into CBs of half vertical and half horizontal size. A quadtree leaf node (e.g., in VVC) may be further partitioned by a binary tree or ternary tree partitioning (or any other partitioning) into CBs of unequal sizes.

[0098] FIG.6 shows example binary tree and ternary tree partitions. A binary tree partition may divide a parent block in half in either a vertical direction 602 or a horizontal direction 604. The resulting partitions may be half in size as compared to the parent block. In other examples, the resulting partitions may correspond to sizes that are less than and / or greater than half of the parent block size. A ternary tree partition may divide a parent block into three parts in either a vertical direction 606 or a horizontal direction 608. FIG.6 shows an example in which the middle partition may be twice as large as the other two end partitions in the ternary tree partitions. In other examples, partitions may be of other sizes relative to each other and to the parent block. Binary and ternary tree partitions are examples of multi-type tree partitioning. Multi-type tree partitions may comprise partitioning a parent block into otherDocket No.: 23-2054PCT quantities of smaller blocks. The block partitioning strategy (e.g., in VVC) may be referred to as a combination of quadtree and multi-type tree partitioning (quadtree + multi-type tree partitioning) because of the addition of binary and / or ternary tree partitioning to quadtree partitioning.

[0099] FIG.7 shows an example of combined quadtree and multi-type tree partitioning of a CTB 700. FIG.8 shows an example tree 800 corresponding to the combined quadtree and multi-type tree partitioning of CTB 700 shown in FIG.7. In both FIGS.7 and 8, quadtree splits are shown in solid lines and multi-type tree splits are shown in dashed lines. For ease of explanation, CTB 700 is shown with the same quadtree partitioning as the CTB 400 described in FIG.4, and a description of the quadtree partitioning of CTB 700, which is similar to that for CTB 400, is omitted. The quadtree partitioning of the CTB 700 is merely an example and a CTB may be quadtree partitioned in a manner different from the CTB 700. Additional multi-type tree partitions of CTB 700 may be made relative to three leaf CBs shown in FIG.4. The three leaf CBs in FIG.4 that are shown in FIG.7 as being further partitioned may be leaf CBs 5, 8, and 9. The three leaf CBs may be further partitioned using one or more binary and / or ternary tree partitions.

[0100] The leaf CB 5 of FIG.4 may be partitioned into two CBs based on a vertical binary tree partitioning. The two resulting CBs may be leaf CBs respectively labeled 5 and 6 in FIGS.7 and 8. The leaf CB 8 of FIG.4 may be partitioned into three CBs based on a vertical ternary tree partition. Two of the three resulting CBs may be leaf CBs respectively labeled 9 and 14 in FIGS.7 and 8. The remaining, non-leaf CB may be partitioned first into two CBs based on a horizontal binary tree partition. One of the two CBs may be a leaf CB labeled 10. The other of the two CBs may be further partitioned into three CBs based on a vertical ternary tree partition. The resulting three CBs may be leaf CBs respectively labeled 11, 12, and 13 in FIGS.7 and 8. The leaf CB 9 of FIG.4 may be partitioned into three CBs based on a horizontal ternary tree partition. Two of the three CBs may be leaf CBs respectively labeled 15 and 19 in FIGS.7 and 8. The remaining, non-leaf CB may be partitioned into three CBs based on another horizontal ternary tree partition. The resulting three CBs may all be leaf CBs respectively labeled 16, 17, and 18 in FIGS.7 and 8.

[0101] Altogether, CTB 700 may be partitioned into 20 leaf CBs respectively labeled 0-19. The 20 leaf CBs may correspond to 20 leaf nodes (e.g., 20 leaf nodes of tree 800 shown in FIG.8). The resulting combination of quadtree and multi-type tree partitioning of the CTB 700 may be scanned using a z-scan (left-to-right, top-to-bottom) to form the sequence order for encoding / decoding the CB leaf nodes. A numeric label of each CB leaf node in FIGS.7 and 8 may correspond to the sequence order for encoding / decoding, with CB leaf node 0 encoded / decoded first and CB leaf node 19 encoded / decoded last. Although not shown in FIGS.7 and 8, it should be noted that each CB leaf node may comprise one or more PBs and / or TBs.

[0102] A coding standard / format (e.g., HEVC, VVC, or any other coding standard / format) may define various units (e.g., in addition to specifying various blocks (e.g., CTBs, CBs, PBs, TBs)). Blocks may comprise a rectangular area of samples in a sample array. Units may comprise the collocated blocks of samples from the different sample arrays (e.g., luma and chroma sample arrays) that form a picture as well as syntax elements and prediction data of the blocks. A coding tree unit (CTU) may comprise the collocated CTBs of the different sample arrays and may form aDocket No.: 23-2054PCT complete entity in an encoded bitstream. A coding unit (CU) may comprise the collocated CBs of the different sample arrays and syntax structures used to code the samples of the CBs. A prediction unit (PU) may comprise the collocated PBs of the different sample arrays and syntax elements used to predict the PBs. A transform unit (TU) may comprise TBs of the different samples arrays and syntax elements used to transform the TBs.

[0103] A block may refer to any of a CTB, CB, PB, TB, CTU, CU, PU, and / or TU (e.g., in the context of HEVC, VVC, or any other coding format / standard). A block may be used to refer to similar data structures in the context of any video coding format / standard / protocol. For example, a block may refer to a macroblock in the AVC standard, a macroblock or a sub-block in the VP8 coding format, a superblock or a sub-block in the VP9 coding format, and / or a superblock or a sub-block in the AV1 coding format.

[0104] In intra prediction, samples of a block to be encoded (e.g., also referred to as a current block) may be predicted from samples of the column immediately adjacent to the left-most column of the current block and samples of the row immediately adjacent to the top-most row of the current block. The samples from the immediately adjacent column and row may be jointly referred to as reference samples. Each sample of the current block may be predicted (e.g., in an intra prediction mode) by projecting the position of the sample in the current block in a given direction to a point along the reference samples. The sample may be predicted by interpolating between the two closest reference samples of the projection point if the projection does not fall directly on a reference sample. A prediction error (e.g., referred to as a residual) may be determined for the current block based on differences between the predicted sample values and the original sample values of the current block.

[0105] Predicting samples and determining a prediction error based on a difference between the predicted samples and original samples may be performed (e.g., at an encoder) for a plurality of different intra prediction modes (e.g., including non-directional intra prediction modes). The encoder may select one of the plurality of intra prediction modes and its corresponding prediction error to encode the current block. The encoder may send an indication of the selected prediction mode and its corresponding prediction error to a decoder for decoding of the current block. The decoder may decode the current block by predicting the samples of the current block, using the intra prediction mode indicated by the encoder, and / or combining the predicted samples with the prediction error.

[0106] FIG.9 shows an example set of reference samples 902 determined for intra prediction of a current block 904. Current block 904 may correspond to a block being encoded and / or decoded. Current block 904 may correspond to block 3 of partitioned CTB 700 as shown in FIG.7. As described herein, the numeric labels 0-19 of the blocks of partitioned CTB 700 may correspond to the sequence order for encoding / decoding the blocks and may be used as such in the example of FIG.9.

[0107] For current block 904 that is w x h samples in size, reference samples 902 may comprise: 2w samples (or any other quantity of samples) of the row immediately adjacent to the top-most row of current block 904, 2h samples (or any other quantity of samples) of the column immediately adjacent to the left-most column of current block 904, and the top left neighboring corner sample to current block 904. Current block 904 may be square, such that w = h = s. In other examples, a current block need not be square, such that w ≠ h. Available samples from neighboring blocksDocket No.: 23-2054PCT of current block 904 may be used for constructing the set of reference samples 902. Samples may not be available for constructing the set of reference samples 902, for example, if the samples lie outside the picture of the current block, the samples are part of a different slice of the current block (e.g., if the concept of slices is used), and / or the samples belong to blocks that have been inter coded and constrained intra prediction is indicated. Intra prediction may not be dependent on inter predicted blocks, for example, if constrained intra prediction is indicated.

[0108] Samples that may not be available for constructing the set of reference samples 902 may comprise samples in blocks that have not already been encoded and reconstructed at an encoder and / or decoded at a decoder based on the sequence order for encoding / decoding. Restriction of such samples from inclusion in the set of reference samples 902 may allow identical prediction results to be determined at both the encoder and decoder. In the example of FIG.9, samples from neighboring blocks 0, 1, and 2 may be available to construct reference samples 902 given that these blocks are encoded and reconstructed at an encoder and decoded at a decoder prior to coding of current block 904. The samples from neighboring blocks 0, 1, and 2 may be available to construct reference samples 902, for example, if there are no other issues (e.g., as mentioned above) preventing the availability of the samples from the neighboring blocks 0, 1, and 2.The portion of reference samples 902 from neighboring block 6 may not be available due to the sequence order for encoding / decoding (e.g., because the block 6 may not have already been encoded and reconstructed at the encoder and / or decoded at the decoder based on the sequence order for encoding / decoding).

[0109] In some examples, unavailable samples from reference samples 902 may be filled with one or more of the available reference samples 902. For example, an unavailable reference sample may be filled with a nearest available reference sample. The nearest available reference sample may be determined by moving in a clock-wise direction through reference samples 902 from the position of the unavailable reference. The reference samples 902 may be filled with the mid-value of the dynamic range of the picture being coded, for example, if no reference samples are available.

[0110] Reference samples 902 may be filtered based on the size of current block 904 being coded and an applied intra prediction mode. FIG.9 shows an example determination of reference samples for intra prediction of a block. Reference samples may be determined in a different manner than described above. For example, multiple reference lines may be used in other instances (e.g., in VVC).

[0111] Samples of current block 904 may be intra predicted based on reference samples 902, for example, based on (e.g., after) determination and (optionally) filtering of reference samples 902. At least some (e.g., most) encoders / decoders may support a plurality of intra prediction modes in accordance with one or more video coding standards. For example, HEVC supports 35 intra prediction modes, including a planar mode, a direct current (DC) mode, and 33 angular modes. VVC supports 67 intra prediction modes, including a planar mode, a DC mode, and 65 angular modes. Planar and DC modes may be used to predict smooth and gradually changing regions of a picture. Angular modes may be used to predict directional structures in regions of a picture. Any quantity of intra prediction modes may be supported.Docket No.: 23-2054PCT

[0112] FIGS.10A and 10B show example intra prediction modes. FIG.10A shows 35 intra prediction modes, such as supported by HEVC. The 35 intra prediction modes may be indicated / identified by indices 0 to 34. Prediction mode 0 may correspond to planar mode. Prediction mode 1 may correspond to DC mode. Prediction modes 2-34 may correspond to angular modes. Prediction modes 2-18 may be referred to as horizontal prediction modes because the principal source of prediction is in the horizontal direction. Prediction modes 19-34 may be referred to as vertical prediction modes because the principal source of prediction is in the vertical direction.

[0113] FIG.10B shows 67 intra prediction modes, such as supported by VVC. The 67 intra prediction modes may be indicated / identified by indices 0 to 66. Prediction mode 0 may correspond to planar mode. Prediction mode 1 corresponds to DC mode. Prediction modes 2-66 may correspond to angular modes. Prediction modes 2-34 may be referred to as horizontal prediction modes because the principal source of prediction is in the horizontal direction. Prediction modes 35-66 may be referred to as vertical prediction modes because the principal source of prediction is in the vertical direction. Some of the intra prediction modes illustrated in FIG.10B may be adaptively replaced by wide-angle directions because blocks in VVC need not be squares.

[0114] FIG.11 shows a current block 904 and corresponding reference samples 902 from FIG.9. To further describe how intra prediction modes are applied to determine a prediction (e.g., a prediction block) of current block 904, FIG.11 shows current block 904 and reference samples 902 in a two-dimensional x, y plane, where a sample may be referenced as p[x][y]. To simplify the prediction process, reference samples 902 may be placed in two, one- dimensional arrays. The reference samples 902, above the current block 904, may be placed in the one-dimensional array ref^[x]:ref^[x] = p[−1 + x][−1], (x ≥ 0). (1)The reference samples 902 to the left of current block 904 may be placed in the one-dimensional array ref^[y]:ref^[y] = p[−1][−1 + y], (y ≥ 0). (2)

[0115] The prediction process may comprise determination of a predicted sample p[x][y] (e.g., a predicted value) at a location [x][y] in current block 904. For planar mode, a sample at the location [x][y] in current block 904 may be predicted by determining / calculating the mean of two interpolated values. The first of the two interpolated values may be based on a horizontal linear interpolation at the location [x][y] in current block 904. The second of the two interpolated values may be based on a vertical linear interpolation at location [x][y] in current block 904. The predicted sample p[x][y] in current block 904 may be determined / calculated as:whereh[x][y] = (s − x − 1) ∙ ref^[y] + (x + 1) ∙ ref^[s] (4)may be the horizonal linear interpolation at the location [x][y] in current block 904 andv[x][y] = (s − y − 1) ∙ ref^[x] + (y + 1) ∙ ref^[s] (5)Docket No.: 23-2054PCT may be the vertical linear interpolation at the location [x][y] in current block 904. s may be equal to a length of a side (e.g., a number of samples on a side) of the current block 904.

[0116] For DC mode, a sample at a location [x][y] in current block 904 may be predicted by the mean of the reference samples 902. The predicted sample p[x][y] in current block 904 may be determined / calculated as: ^^^ ref^[x] + ^ ref^[y]".(6)!^

[0117] For angular modes, a sample at a location [x][y] in current block 904 may be predicted by projecting the location [x][y] in a direction specified by a given angular mode to a point on the horizontal or vertical line of samples comprising reference samples 902. The sample at the location [x][y] may be predicted by interpolating between the two closest reference samples of the projection point if the projection does not fall directly on a reference sample. The direction specified by the angular mode may be given by an angle φ defined relative to the y-axis for vertical prediction modes (e.g., modes 19-34 in HEVC and modes 35-66 in VVC). The direction specified by the angular mode may be given by an angle φ defined relative to the x-axis for horizontal prediction modes (e.g., modes 2-18 in HEVC and modes 2-34 in VVC).

[0118] FIG.12 shows an example applying an intra prediction mode (e.g., an angular mode such as vertical prediction mode 906) for prediction of a current block 904. FIG.12 specifically shows prediction of a sample at a location [x][y] in current block 904 for a vertical prediction mode 906. Vertical prediction mode 906 may be given by an angle φ with respect to the vertical axis. The location [x][y] in current block 904, in vertical prediction modes, may be projected to a point (e.g., referred to as a projection point) on the horizontal line of reference samples ref^[x]. The reference samples 902 are only partially shown in FIG.12 for ease of illustration. As shown in FIG.12, the projection point on the horizontal line of reference samples ref^[x] may not be exactly on a reference sample. A predicted sample p[x][y] in current block 904 may be determined / calculated by linearly interpolating between the two reference samples, for example, if the projection point falls at a fractional sample position between two reference samples. The predicted sample p[x][y] may be determined / calculated as:p[x][y] = (1 − i%) ∙ ref^[x + i& + 1] + i% ∙ ref^[x + i& + 2]. (7)i& may be the integer part of the horizontal displacement of the projection point relative to the location [x][y]. i& maybe determined / calculated as a function of the tangent of the angle φ of the vertical prediction mode 906 as:i& = ⌊(y + 1) ∙ tan φ⌋. (8)i% may be the fractional part of the horizontal displacement of the projection point relative to the location [x][y] andmay be determined / calculated as:i% = ((y + 1) ∙ tan φ) − ⌊(y + 1) ∙ tan φ⌋, (9)where⌊∙⌋is the integer floor function.Docket No.: 23-2054PCT

[0119] For horizontal prediction modes, a location [x][y] of a sample in current block 904 may be projected onto the vertical line of reference samples ref^[y]. A predicted sample p[x][y]for horizontal prediction modes may be determined / calculated as:p[x][y] = (1 − i%) ∙ ref^[y + i& + 1] + i% ∙ ref^[y + i& + 2]. (10)i& may be the integer part of the vertical displacement of the projection point relative to the location [x][y]. i&may bedetermined / calculated as a function of the tangent of the angle φ of the horizontal prediction mode as:i& = ⌊(x + 1) ∙ tan φ⌋. (11)i% may be the fractional part of the vertical displacement of the projection point relative to the location [x][y]. i% maybe determined / calculated as:i% = ((x + 1) ∙ tan φ) − ⌊(x + 1) ∙ tan φ⌋, (12)where⌊∙⌋is the integer floor function.

[0120] The interpolation functions given by Equations (7) and (10) may be implemented by an encoder and / or a decoder (e.g., encoder 200 in FIG.2 and / or decoder 300 in FIG.3). The interpolation functions may be implemented by finite impulse response (FIR) filters. For example, the interpolation functions may be implemented as a set of two- tap FIR filters. The coefficients of the two-tap FIR filters may be respectively given by (1-i%) and i%. The predicted sample p[x][y], in angular intra prediction, may be calculated with some predefined level of sample accuracy (e.g., 1 / 32 sample accuracy, or accuracy defined by any other metric). For 1 / 32 sample accuracy, the set of two-tap FIR interpolation filters may comprise up to 32 different two-tap FIR interpolation filters — one for each of the 32 possible values of the fractional part of the projected displacement i%. In other examples, different levels of sample accuracy may be used.

[0121] In some examples, the FIR filters may be used for predicting chroma samples and / or luma samples. For example, the two-tap interpolation FIR filter may be used for predicting chroma samples and a same and / or a different interpolation technique / filter may be used for luma samples. For example, a four-tap FIR filter may be used to determine a predicted value of a luma sample. Coefficients of the four tap FIR filter may be determined based on i%(e.g., similar to the two-tap FIR filter). For 1 / 32 sample accuracy, a set of 32 different four-tap FIR filters may comprise up to 32 different four-tap FIR filters — one for each of the 32 possible values of the fractional part of the projected displacement i%. In other examples, different levels of sample accuracy may be used. The set of four-tap FIR filters may be stored in a look-up table (LUT) and referenced based on i%. A predicted sample p[x][y], for vertical prediction modes, may be determined based on the four-tap FIR filter as: 0 (13) p[x][y] = ^ fT[i] ∙ ref^[x + iIdx + i] ,&^where fT[i], i = 0...3, may be the filter coefficients, and Idx is integer displacement. A predicted sample p[x][y], for horizontal prediction modes, may be determined based on the four-tap FIR filter as:Docket No.: 23-2054PCT (14) iIdx + i] .

[0122] Supplementary reference samples may be determined / constructed if the location [x][y] of a sample in current block 904 to be predicted is projected to a negative x coordinate. The location [x][y] of a sample may be projected to a negative x coordinate, for example, if negative vertical prediction angles φ are used. The supplementary reference samples may be determined / constructed by projecting the reference samples in ref^[y] in the vertical line of reference samples 902 to the horizontal line of reference samples 902 using the negative vertical prediction angle φ. Supplementary reference samples may be similarly determined / constructed, for example, if the location [x][y] of a sample in current block 904 to be predicted is projected to a negative y coordinate. The location[x][y] of a sample may be projected to a negative y coordinate, for example, if negative horizontal prediction anglesφ are used. The supplementary reference samples may be determined / constructed by projecting the reference samples in ref^[x] on the horizontal line of reference samples 902 to the vertical line of reference samples 902 using the negative horizontal prediction angle φ.

[0123] An encoder may determine / predict samples of a current block being encoded (e.g., current block 904) for a plurality of intra prediction modes (e.g., using one or more of the functions described herein). For example, an encoder may determine / predict samples of a current block for each of 35 intra prediction modes in HEVC and / or 67 intra prediction modes in VVC. The encoder may determine, for each intra prediction mode applied, a corresponding prediction error for the current block based on a difference (e.g., sum of squared differences (SSD), sum of absolute differences (SAD), or sum of absolute transformed differences (SATD)) between the prediction samples determined for the intra prediction mode and the original samples of the current block. The encoder may determine / select one of the intra prediction modes to encode the current block based on the determined prediction errors. For example, the encoder may determine / select one of the intra prediction modes that results in the smallest prediction error for the current block. In some examples, the encoder may determine / select the intra prediction mode to encode the current block based on a rate-distortion measure (e.g., Lagrangian rate-distortion cost) determined using the prediction errors. The encoder may send an indication of the determined / selected intra prediction mode and its corresponding prediction error (e.g., residual) to a decoder for decoding of the current block.

[0124] A decoder may determine / predict samples of a current block being decoded (e.g., current block 904) for an intra prediction mode. For example, a decoder may receive an indication of an intra prediction mode (e.g., an angular intra prediction mode) from an encoder for a current block. The decoder may construct a set of reference samples and perform intra prediction based on the intra prediction mode indicated by the encoder for the current block in a similar manner (e.g., as described above for the encoder). The decoder may add predicted values of the samples (e.g., determined based on the intra prediction mode) of the current block to a residual of the current block to reconstruct the current block. In some examples, a decoder need not receive an indication of an angular intra prediction mode from an encoder for a current block. Instead, the decoder may determine an intra prediction mode through other, decoder-side means.Docket No.: 23-2054PCT

[0125] While various examples herein correspond to intra prediction modes in HEVC and VVC, the methods, devices, and systems as described herein may be applied to / used for other intra prediction modes (e.g., as used in other video coding standards / formats, such as VP8, VP9, AV1, etc.).

[0126] Intra prediction may exploit correlations between spatially neighboring samples in the same picture of a video sequence to perform video compression. Inter prediction is another coding tool that may be used to perform video compression. Inter prediction may exploit correlations in the time domain between blocks of samples in different pictures of a video sequence. For example, an object may be seen across multiple pictures of a video sequence. The object may move (e.g., by some translation and / or affine motion) or remain stationary across the multiple pictures. A current block of samples in a current picture being encoded may have / be associated with a corresponding block of samples in a previously decoded picture. The corresponding block of samples may accurately predict the current block of samples. The corresponding block of samples may be displaced from the current block of samples, for example, due to movement of the object, represented in both blocks, across the respective pictures of the blocks. The previously decoded picture may be a reference picture. The corresponding block of samples in the reference picture may be a reference block for motion compensated prediction. An encoder may use a block matching technique to estimate the displacement (or motion) of the object and / or to determine the reference block in the reference picture.

[0127] Similar to intra prediction, an encoder may determine a difference between a current block and a prediction for a current block. An encoder may determine a difference, for example, based on / after determining / generating a prediction for a current block (e.g., using inter prediction). The difference may be a prediction error (e.g., a residual). The encoder may store and / or send (e.g., signal), in / via a bitstream, the prediction error and / or other related prediction information. The prediction error and / or other related prediction information may be used for decoding and / or other forms of consumption. A decoder may decode the current block by predicting the samples of the current block (e.g., by using the related prediction information) and combining the predicted samples with the prediction error.

[0128] FIG.13A shows an example of inter prediction. The inter prediction may be performed for a current block 1300 in a current picture 1302 being encoded. An encoder (e.g., encoder 200 as shown in FIG.2) may perform inter prediction to determine and / or generate a reference block 1304 in a reference picture 1306. Reference block 1304 may be used to predict the current block 1300. Reference pictures (e.g., reference picture 1306) may be prior decoded pictures available at the encoder and / or a decoder. Availability of a prior decoded picture may depend / be based on whether the prior decoded picture is available in a decoded picture buffer, at the time, current block 1300 is being encoded and / or decoded. The encoder may search the one or more reference pictures 1306 for a block (e.g., a candidate reference block) that is similar (or substantially similar) to current block 1300. The encoder may determine the best matching block from the blocks (e.g., candidate reference blocks) tested during the searching process. The best matching block may be a reference block 1304. The encoder may determine that reference block 1304 is the best matching reference block based on one or more cost criteria. The one or more cost criteria may comprise a rate- distortion criterion (e.g., Lagrangian rate-distortion cost). The one or more cost criteria may be based on a differenceDocket No.: 23-2054PCT (e.g., SSD, SAD, and / or SATD) between prediction samples of reference block 1304 and original samples of current block 1300.

[0129] The encoder may search for reference block 1304 within a reference region (e.g., a search range 1308). The reference region (e.g., a search range 1308) may be positioned around a collocated block (or position) 1310, of current block 1300, in reference picture 1306. Collocated block 1310 may have a same position in the reference picture 1306 as the current block 1300 in the current picture 1302. The reference region (e.g., search range 1308) may at least partially extend outside of reference picture 1306. Constant boundary extension may be used, for example, if the reference region (e.g., search range 1308) extends outside of reference picture 1306. The constant boundary extension may be used such that values of the samples in a row or a column of reference picture 1306, immediately adjacent to a portion of the reference region (e.g., search range 1308) extending outside of reference picture 1306, may be used for sample locations outside of reference picture 1306. A subset of potential positions, or all potential positions, within the reference region (e.g., search range 1308) may be searched for reference block 1304. The encoder may utilize one or more search implementations to determine and / or generate the reference block 1304. For example, the encoder may determine a set of candidate search positions based on motion information of neighboring blocks (e.g., a motion vector 1312) to the current block 1300.

[0130] One or more reference pictures may be searched by the encoder during inter prediction to determine and / or generate the best matching reference block. The reference pictures searched by the encoder may be included in (e.g., added to) one or more reference picture lists. For example, in HEVC and VVC (and / or in one or more other communication protocols), two reference picture lists may be used (e.g., a reference picture list 0 and a reference picture list 1). A reference picture list may include one or more pictures. The reference picture 1306 of reference block 1304 may be indicated by a reference index pointing into a reference picture list comprising reference picture 1306.

[0131] FIG.13B shows an example motion vector. A displacement between reference block 1304 and current block 1300 may be interpreted as an estimate of the motion between reference block 1304 and current block 1300 across their respective pictures. The displacement may be represented by a motion vector 1312. For example, motion vector 1312 may be indicated by a horizontal component (MVx) and a vertical component (MVy) relative to the position of current block 1300. A motion vector (e.g., motion vector 1312) may have fractional or integer resolution. A motion vector with fractional resolution may point between two samples in a reference picture to provide a better estimation of the motion of current block 1300. For example, a motion vector may have 1 / 2, 1 / 4, 1 / 8, 1 / 16, 1 / 32, or any other fractional sample resolution. Interpolation between the two samples at integer positions may be used to generate a reference block and its corresponding samples at fractional positions, for example, if a motion vector points to a non- integer sample value in the reference picture. The interpolation may be performed by a filter with two or more taps.

[0132] The encoder may determine a difference (e.g., a corresponding sample-by-sample difference) between reference block 1304 and current block 1300. The encoder may determine the difference between reference block 1304 and current block 1300, for example, based on / after reference block 1304 is determined and / or generated, using inter prediction, for current block 1300. The difference may be a prediction error (e.g., a residual). The encoderDocket No.: 23-2054PCT may store and / or send (e.g., signal), in / via a bitstream, the prediction error and / or related motion information. The prediction error and / or the related motion information may be used for decoding (e.g., decoding current block 1300) and / or other forms of consumption. The motion information may comprise the motion vector 1312 and a reference indicator / index. The reference indicator may indicate the reference picture 1306 in a reference picture list. In other examples, the motion information may comprise an indication of motion vector 1312 and / or an indication of the reference indicator / index. The reference indicator may indicate reference picture 1306 in the reference picture list comprising reference picture 1306. A decoder may decode current block 1300 by determining and / or generating the reference block 1304, which may correspond to / form (e.g., be considered as) a prediction of the current block 1300. The decoder may determine and / or generate the reference block 1304, for example, based on the related motion information. The decoder may decode current block 1300 based on combining the prediction (e.g., a reference block) with the prediction error (e.g., a residual block).

[0133] Inter prediction, as shown in FIG.13A, may be performed using one reference picture 1306 as a source of a prediction for current block 1300. Inter prediction based on a prediction of a current block using a single picture may be referred to as uni-prediction.

[0134] Inter prediction of a current block, using bi-prediction, may be based on two pictures (e.g., the source of prediction may be from the two pictures). Bi-prediction may be useful, for example, if a video sequence comprises fast motion, camera panning, zooming, and / or scene changes. Bi-prediction also may be useful to capture fade outs of one scene or fade outs from one scene to another, where two pictures may effectively be displayed simultaneously with different levels of intensity.

[0135] One or both of uni-prediction and bi-prediction may be available / used for performing inter prediction (e.g., at an encoder and / or at a decoder). Performing a specific type of inter prediction (e.g., uni-prediction and / or bi- prediction) may depend on a slice type of current block. For example, for P slices, only uni-prediction may be available / used for performing inter prediction. For B slices, either uni-prediction or bi-prediction may be available / used for performing inter prediction. An encoder may determine and / or generate a reference block, for predicting a current block, from a reference picture list 0, for example, if the encoder is using uni-prediction. An encoder may determine and / or generate a first reference block, for predicting a current block, from a reference picture list 0 and determine and / or generate a second reference block, for predicting the current block, from a reference picture list 1, for example, if the encoder is using bi-prediction.

[0136] FIG.14 shows an example of bi-prediction. Two reference blocks 1402 and 1404 may be used to predict a current block 1400. Reference block 1402 may be in a reference picture of one of reference picture list 0 or reference picture list 1. Reference block 1404 may be in a reference picture of another one of reference picture list 0 or reference picture list 1. As shown in FIG.14, reference block 1402 may be in a first picture that precedes (e.g., in time) a current picture of current block 1400, and the reference block 1404 may be in a second picture that succeeds (e.g., in time) the current picture of current block 1400. The first picture may precede the current picture in terms of a picture order count (POC). The second picture may succeed the current picture in terms of the POC. In otherDocket No.: 23-2054PCT examples, the reference pictures may both precede or both succeed the current picture in terms of POC. A POC may be / indicate an order in which pictures are output (e.g., from a decoded picture buffer). A POC may be / indicate an order in which pictures are generally intended to be displayed. Pictures that are output may not necessarily be displayed but may undergo different processing and / or consumption (e.g., transcoding). The two reference blocks determined and / or generated using / for bi-prediction may correspond to (e.g., be comprised in) a same reference picture. The reference picture may be included in both the reference picture list 0 and the reference picture list 1, for example, if the two reference blocks correspond to the same reference picture.

[0137] A configurable weight and / or offset value may be applied to one or more inter prediction reference blocks. An encoder may enable the use of weighted prediction using a flag in a picture parameter set (PPS). The encoder may send / signal the weight and / or offset parameters in a slice segment header for current block 1400. Different weight and / or offset parameters may be sent / signaled for luma and / or chroma components.

[0138] The encoder may determine and / or generate the reference blocks 1402 and 1404 for the current block 1400 using inter prediction. The encoder may determine a difference between current block 1400 and each of reference blocks 1402 and 1404. The differences may be prediction errors or residuals. The encoder may store and / or send / signal, in / via a bitstream, the prediction errors and / or their respective related motion information. The prediction errors and their respective related motion information may be used for decoding and / or other forms of consumption.

[0139] The motion information for reference block 1402 may comprise a motion vector 1406 and / or a reference indicator / index. The reference indicator may indicate a reference picture, of the reference block 1402, in a reference picture list. In some examples, the motion information for reference block 1402 may comprise an indication of motion vector 1406 and / or an indication of the reference index. The reference index may indicate the reference picture, of reference block 1402, in the reference picture list.

[0140] The motion information for reference block 1404 may comprise a motion vector 1408 and / or a reference index / indicator. The reference indicator may indicate a reference picture, of the reference block 1404, in a reference picture list. The motion information for reference block 1404 may comprise an indication of motion vector 1408 and / or an indication of the reference index. The reference index may indicate the reference picture, of the reference block 1404, in the reference picture list.

[0141] A decoder may decode current block 1400 by determining and / or generating the reference blocks 1402 and 1404. The decoder may determine and / or generate the reference blocks 1402 and 1404, for example, based on the respective related motion information for the reference blocks 1402 and 1404. The reference blocks 1402 and 1404 may correspond to / form (e.g., be considered as) the prediction (e.g., used to generate a prediction block) of the current block 1400. The decoder may decode the current block 1400 based on combining the prediction with the prediction errors.

[0142] Motion information may be predictively coded, for example, before being stored and / or sent / signaled in / via a bit stream (e.g., in HEVC, VVC, and / or other video coding standards / formats / protocols). The motion information for a current block may be predictively coded based on motion information of one or more blocks neighboring the currentDocket No.: 23-2054PCT block. The motion information of the neighboring block(s) may often correlate with the motion information of the current block because the motion of an object represented in the current block is often the same as (or similar to) the motion of objects in the neighboring block(s). Motion information prediction techniques (such as those in HEVC and VVC) may comprise advanced motion vector prediction (AMVP) and / or inter prediction block merging (e.g., merge mode).

[0143] An encoder (e.g., encoder 200 as shown in FIG.2), may code a motion vector. The encoder may code the motion vector (e.g., using AMVP) as a difference between a motion vector of a current block being coded and a motion vector predictor (MVP). An encoder may determine / select the MVP from a list of candidate MVPs. The candidate MVPs may be / correspond to previously decoded motion vectors of neighboring blocks in the current picture of the current block, and / or blocks at or near the collocated position of the current block in other reference pictures. The encoder and / or a decoder may reciprocally generate and / or determine the list of candidate MVPs.

[0144] The encoder may determine / select an MVP from the list of candidate MVPs. Then, the encoder may send / signal, in / via a bitstream, an indication of the selected MVP and / or a motion vector difference (MVD). The encoder may indicate the selected MVP in the bitstream using an index / indicator. The index may indicate the selected MVP in the list of candidate MVPs. The MVD may be determined / calculated based on a difference between the motion vector of the current block and the selected MVP. For example, for a motion vector (e.g., comprising a horizontal component (MVx) and a vertical component (MVy)) that indicates a position relative to a position of the current block being coded, the MVD may be represented by two components MVD^and MVD!. MVD^and MVD!may be determined / calculated as:MVD^ = MV^ − MVP^, (15)MVD! = MV! − MVP!. (16)MVDx and MVDy may respectively represent horizontal and vertical components of the MVD. MVPx and MVPy may respectively represent horizontal and vertical components of the MVP.

[0145] A decoder (e.g., decoder 300 as shown in FIG.3) may decode the motion vector by adding the MVD to the MVP indicated in / via the bitstream. The decoder may decode the current block by determining and / or generating the reference block. The decoder may determine and / or generate the reference block, for example, based on the decoded motion vector. The reference block may correspond to / form (e.g., be considered as) the prediction of the current block (e.g., a prediction block). The decoder may decode the current block by combining the prediction with the prediction error.

[0146] The list of candidate MVPs (e.g., in HEVC, VVC, and / or one or more other communication protocols), for AMVP, may comprise two or more candidates (e.g., candidates A and B). Candidates A and B may comprise: up to two (or any other quantity of) spatial candidate MVPs determined / derived from five (or any other quantity of) spatial neighboring blocks of a current block being coded; one (or any other quantity of) temporal candidate MVP determined / derived from two (or any other quantity of) temporal, co-located blocks (e.g., if both of the two spatial candidate MVPs are not available or are identical); and / or zero motion vector candidate MVPs (e.g., if one or both ofDocket No.: 23-2054PCT the spatial candidate MVPs or temporal candidate MVPs are not available). Other quantities of spatial candidate MVPs, spatial neighboring blocks, temporal candidate MVPs, and / or temporal, co-located blocks may be used for the list of candidate MVPs.

[0147] FIG.15A shows example spatial candidate neighboring blocks for a current block. For example, five (or any other quantity of) spatial candidate neighboring blocks may be located relative to a current block 1500 being encoded. The five spatial candidate neighboring blocks may be A0, A1, B0, B1, and B2. FIG.15B shows temporal, co-located blocks for the current block. For example, two (or any other quantity of) temporal, co-located blocks may be located relative to current block 1500 being coded. The two temporal, co-located blocks may be C0 and C1. The two temporal, co-located blocks may be in one or more reference pictures that may be different from the current picture of current block 1500.

[0148] An encoder (e.g., encoder 200 as shown in FIG.2) may code a motion vector using inter prediction block merging (e.g., a merge mode). For example, the encoder (e.g., using merge mode) may reuse the same motion information of a neighboring block (e.g., one of neighboring blocks A0, A1, B0, B1, and B2) for inter prediction of a current block. For example, the encoder (e.g., using merge mode) may reuse the same motion information of a temporal, co-located block (e.g., one of temporal, co-located blocks C0 and C1) for inter prediction of a current block. An MVD need not be sent (e.g., indicated, signaled) for the current block because the same motion information as that of a neighboring block or a temporal, co-located block may be used for the current block (e.g., at the encoder and / or a decoder). A signaling overhead for sending / signaling the motion information of the current block may be reduced because the MVD need not be indicated for the current block. The encoder and / or the decoder may reciprocally generate a candidate list of motion information from neighboring blocks or temporal, co-located blocks of the current block (e.g., in a manner similar to AMVP). The encoder may determine to use (e.g., inherit) motion information, of one neighboring block or one temporal, co-located block in the candidate list, for predicting motion information of the current block being coded. The encoder may signal / send, in / via a bitstream, an indication of the determined motion information from the candidate list. For example, the encoder may signal / send an indicator / index. The index may indicate the determined motion information in the list of candidate motion information. The encoder may signal / send the index to indicate the determined motion information.

[0149] A list of candidate motion information for merge mode (e.g., in HEVC, VVC, or any other coding formats / standards / protocols) may comprise: up to four (or any other quantity of) spatial merge candidates derived / determined from five (or any other quantity of) spatial neighboring blocks (e.g., as shown in FIG.15A); one (or any other quantity of) temporal merge candidate derived from two (or any other quantity of) temporal, co-located blocks (e.g., as shown in FIG.15B); and / or additional merge candidates comprising bi-predictive candidates and zero motion vector candidates. In some examples, the spatial neighboring blocks and the temporal, co-located blocks used for merge mode may be the same as the spatial neighboring blocks and the temporal, co-located blocks used for AMVP.Docket No.: 23-2054PCT

[0150] Inter prediction may be performed in other ways and variants than those described herein. For example, motion information prediction techniques other than AMVP and merge mode may be used. While various examples herein correspond to inter prediction modes, such as used in HEVC and VVC, the methods, devices, and systems as described herein may be applied to / used for other inter prediction modes (e.g., as used for other video coding standards / formats such as VP8, VP9, AV1, etc.). History based motion vector prediction (HMVP), combined intra / inter prediction mode (CIIP), and / or merge mode with motion vector difference (MMVD) (e.g., as described in VVC) may be performed / used and are within the scope of the present disclosure.

[0151] A block matching operation (or technique) may be applied / used (e.g., in inter prediction) to determine a reference block in a different picture than that of a current block being coded (e.g., encoded and / or decoded). A block matching operation also may be applied / used to determine a reference block in a same picture as that of a current block being coded. The reference block, in a same picture as that of the current block, as determined using block matching may often not accurately predict the current block (e.g., for camera captured videos). Prediction accuracy for screen content videos may not be similarly impacted, for example, if a reference block in the same picture as that of the current block is used for encoding. Screen content videos may comprise, for example, computer generated text, graphics, animation, etc. Screen content videos may comprise (e.g., may often comprise) repeated patterns (e.g., repeated patterns of text and / or graphics) within the same picture. Using a reference block (e.g., as determined using block matching), in a same picture as that of a current block being encoded, may provide efficient compression for screen content videos.

[0152] A prediction technique may be used (e.g., in HEVC, VVC, and / or any other coding standards / formats / protocols) to exploit correlation between blocks of samples within a same picture (e.g., of screen content videos). The prediction technique may be intra block copy (IBC) or current picture referencing (CPR). An encoder may apply / use a block matching technique (e.g., similar to inter prediction) to determine a displacement vector (e.g., a block vector (BV)). The BV may indicate a relative position of a reference block (e.g., in accordance with intra block compensated prediction), that best matches the current block, from a position of the current block. For example, the relative position of the reference block may be a relative position of a top-left corner (or any other point / sample) of the reference block. The BV may indicate a relative displacement from the current block to the reference block that best matches the current block. The encoder may determine the best matching reference block from blocks tested during a searching process (e.g., in a manner similar to that used for inter prediction). The encoder may determine that a reference block is the best matching reference block based on one or more cost criteria. The one or more cost criteria may comprise a rate-distortion criterion (e.g., Lagrangian rate-distortion cost). The one or more cost criteria may be based on, for example, one or more differences (e.g., an SSD, an SAD, an SATD, and / or a difference determined based on a hash function) between the prediction samples of the reference block and the original samples of the current block. A reference block may correspond to / comprise prior decoded blocks of samples (e.g., reconstructed samples) of the current picture. The reference block may comprise decoded blocks of samples of the current picture prior to being processed by in-loop filtering operations (e.g., deblocking and / or SAO filtering).Docket No.: 23-2054PCT

[0153] FIG.16 shows an example of IBC (e.g., an IBC mode). The example shown in FIG.16 may correspond to screen content. The rectangular portions / sections with arrows beginning at their boundaries may be the current blocks being encoded. The rectangular portions / sections that the arrows point to may be the reference blocks for predicting the respective current blocks.

[0154] A reference block may be determined and / or generated, for a current block, using IBC. The encoder may determine a difference (e.g., a corresponding sample-by-sample difference) between the reference block and the current block. The difference may be a prediction error or residual. The encoder may store and / or send / signal, in / via a bitstream the prediction error and / or related prediction information. The prediction error and / or the related prediction information may be used for decoding and / or other forms of consumption. The prediction information may comprise a BV. The prediction information may comprise an indication of the BV. A decoder (e.g., decoder 300 as shown in FIG. 3), may decode the current block by determining and / or generating the reference block. The decoder may determine and / or generate the current block, for example, based on the prediction information (e.g., the BV). The reference block may correspond to / form (e.g., be considered as) the prediction (e.g., a prediction block) of the current block. The decoder may decode the current block by combining the prediction (e.g., prediction block) with the prediction error (e.g., residual or residual block).

[0155] A BV may be predictively coded (e.g., in HEVC, VVC, and / or any other coding standards / formats / protocols) before being stored and / or sent / signaled in / via a bitstream. For example, the BV for a current block may be predictively coded based on a BV of one or more blocks neighboring the current block. For example, an encoder may predictively code a BV using the merge mode (e.g., in a manner similar to as described herein for inter prediction), AMVP (e.g., as described herein for inter prediction), or a technique similar to AMVP. The technique similar to AMVP may be BV prediction and difference coding (or AMVP for IBC).

[0156] An encoder (e.g., encoder 200 as shown in FIG.2) performing BV prediction and coding may code a BV as a difference between the BV of a current block being coded and a block vector predictor (BVP). An encoder may select / determine the BVP from a list of candidate BVPs. The candidate BVPs may comprise / correspond to previously decoded BVs of neighboring blocks in the current picture of the current block. The encoder and / or a decoder may reciprocally generate or determine the list of candidate BVPs.

[0157] The encoder may send / signal, in / via a bitstream, an indication of the selected BVP and a block vector difference (BVD). The encoder may indicate the selected BVP in the bitstream using an index / indicator. The index may indicate (e.g., point to) the selected BVP in the list of candidate BVPs. The BVD may be determined / calculated based on a difference between a BV of the current block and the selected BVP. For example, for a BV (e.g., represented by a horizontal component (BVx) and a vertical component (BVy)) that indicates a position relative to a position of the current block being coded, the BVD may be represented by two components BVD^and BVD!. BVD^and BVD! may be determined / calculated as:BVD^ = BV^ − BVP^, (17)Docket No.: 23-2054PCT BVD! = BV! − BVP!. (18)BVDx and BVDy may respectively represent horizontal and vertical components of the BVD. BVPx and BVPy may respectively represent horizontal and vertical components of the BVP. A decoder (e.g., decoder 300 as shown in FIG. 3), may decode the BV by adding the BVD to the BVP indicated in / via the bitstream. The decoder may decode the current block by determining and / or generating the reference block. The decoder may determine and / or generate the reference block, for example, based on the decoded BV. The reference block may correspond to / form (e.g., be considered as) the prediction (e.g., a prediction block) of the current block. The decoder may decode the current block by combining the prediction (e.g., the prediction block) with the prediction error (e.g., residual or residual block).

[0158] A same BV as that of a neighboring block may be used for the current block and a BVD need not be separately signaled / sent for the current block, such as in the merge mode. A BVP (in the candidate BVPs), which may correspond to a decoded BV of the neighboring block, may itself be used as a BV for the current block. Not sending the BVD may reduce the signaling overhead.

[0159] A list of candidate BVPs (e.g., in HEVC, VVC, and / or any other coding standard / format / protocol) may comprise two (or more) candidates. The candidates may comprise candidates A and B. Candidates A and B may comprise: up to two (or any other quantity of) spatial candidate BVPs determined / derived from five (or any other quantity of) spatial neighboring blocks of a current block being encoded; and / or one or more of last two (or any other quantity of) coded BVs (e.g., if spatial neighboring candidates are not available). Spatial neighboring candidates may not be available, for example, if neighboring blocks are encoded using intra prediction or inter prediction. Locations of the spatial candidate neighboring blocks, relative to a current block, being encoded using IBC may be illustrated in a manner similar to spatial candidate neighboring blocks used for coding motion vectors in inter prediction (e.g., as shown in FIG.15A). For example, five spatial candidate neighboring blocks of a current block being coded using IBC may be respectively denoted A0, A1, B0, B1, and B2 as shown in FIG.15A.

[0160] Local illumination compensation (LIC) is a prediction technique proposed for reducing prediction errors of prediction blocks generated for coding blocks (e.g., a current block). LIC models illumination variation between a current block and its reference block as a function of illumination variation between a current block template and a reference block template. The parameters of the LIC model (e.g., LIC function) are denoted by a scale α and an offset β, to form the linear equation (19) (shown below) that is used to compensate illumination variations in the reference block. Pref is a sample (e.g., a reference sample) in the reference block pointed to by a displacement vector (motion vector (MV)) in inter prediction. Ppred is a predicted samples corresponding to the reference sample (Pref) being filtered, e.g., in accordance with illumination variation modeled by the parameters scale α and offset β.P6789 = α ∗ P78% − β (19)

[0161] The parameters α and β (e.g., also referred to as coefficients or LIC parameters) are derived based on a template associated with the current block (referred to as current block template or current template) and a corresponding template associated with the reference block (referred to as reference block template or referenceDocket No.: 23-2054PCT template). Consequently, LIC incurs no additional signaling overhead, other than for an LIC flag that may be signaled to indicate the use of LIC.

[0162] The application of LIC to the reference block associated with a current block comprises adjusting reference samples by multiplying the reference samples (respectively the values of the samples) with α (respectively with a value of α) and adding β (respectively a value of β) in accordance with the above-described linear equation (19) for compensating for local illumination differences. The parameters α and β are derived from samples in the templates of the current block and the reference block to reduce differences between samples of the current template and filtered samples of the reference template. For example, a least mean squares method may be used to select (e.g., determine or derive) the parameters to reduce the differences, but other methods such as SAD, SATD, SSE, etc. may be used as well. The parameters α and β can be derived using all, a subset, or subsets of samples in the templates.

[0163] FIG.17A shows an example of a current block and a reference block with their corresponding templates that are used in determining α and β for LIC for inter prediction, according to some embodiments. A current block 1704 is shown in a current picture 1702 and a reference block 1708 is shown in a reference picture 1706. In an example sequence of pictures, the current block 1704 may correspond to the current block 1400 shown in FIG.14 and the reference block 1708 may correspond to either reference block 1402 or reference block 1404. Corresponding templates 1714 and 1716 are shown in relation to the current block 1704 and reference block 1708, respectively. The current template 1714 comprises neighboring samples adjacent to the current block boundary (current block border) 1710 at the left edge and the top edge of the current block 1704. The length of the current template 1714 is the sum of the lengths of the left column and the top row of samples in the current block 1704. The reference template 1716 comprises neighboring samples adjacent to the reference block boundary (reference block border) 1712 at the left edge and the top edge of the reference block 1708. The length of the reference template 1716 is the sum of the lengths of the left column and the top row of samples in the reference block 1708. Templates 1714 and 1716 matches in size, shape, and orientation. For example, templates 1714 and 1716 may have a height of 1 sample (i.e., the left portion of each template 1714 and 1716 is a singe column of samples, and the top portion of each template 1714 and 1716 is a single row of samples).

[0164] The scale parameter, α, can be determined by: ?∑ A (&) ( ) ∑ ( ) ∑scale = BCD ABCE & ^ ABCD & ABCE(&)F . (20)? ∑ A (&)^(∑ A )FBCD BCD(&)

[0165] The offset parameter, β, can be determined by offset

[0166] In the above two equations (20) and (21), n is the number of samples, Trec(i) is the ithsample of the current template (as noted above, the current template is the template of the current block), and Tref(i) is the ithsample of the reference template (as noted above, the reference template is the template of the reference block). The current block may also be referred to as the reconstructed block when decoded by the decoder. It will be noted that when the current block 1704 is yet to be reconstructed, the neighboring blocks (to which the samples of the current templateDocket No.: 23-2054PCT 1714 belong) adjacent to the left edge and the top edge of the current block 1704 have been reconstructed. Samples of reference template 1716 and current template 1714 are reconstructed samples of reference picture 1706 and current picture 1702, respectively.

[0167] FIG.17B shows a method 1720 to generate (e.g., calculate) a prediction block when performing inter prediction using LIC, according to some embodiments. Method 1720 may be performed at an encoder (e.g., encoder 200 of FIG.2) and / or at a decoder (e.g., decoder 300 of FIG.3).

[0168] At operation 1722, template samples for the current block and the reference block are obtained. LIC uses a one-tap filter model 1718 to sample templates 1714 and 1716. The one-tap filter model 1718 is used to obtain each respective template sample i from the same relative position in the two templates 1714 and 1716.

[0169] At operation 1724, the template samples (e.g., neighbor samples of the reference block and the current block) are used in the equation (20) to calculate the scale parameter. In some implementations, as shown above in equation (21), the offset parameter is calculated using the calculated scale parameter. Accordingly, an LIC filter may be determined that corresponds to the one-tap LIC model with the calculated scale and offset parameters.

[0170] In some examples, after scale α and offset β parameters are determined by applying the one-tap filter model 1718 to the current template 1714 and the reference template 1716, at operation 1726, they (i.e., scale α and offset β) are applied to respective reference samples Pref to obtain prediction samples Ppred (samples of the prediction block) in accordance with the equation (19) shown above.

[0171] When method 1720 is used at an encoder, the thus determined prediction block may be subtracted from the current block to obtain the prediction errors (e.g., residual or a residual block) that are subsequently encoded in a bitstream. When method 1720 is used at a decoder, the prediction error received in the bitstream may be added to the thus determined prediction block to obtain (e.g., reconstruct) the current block. The prediction block determined based on LIC may have improved illumination variation relative to the reference block and may consequently yield smaller prediction errors that need to be encoded in the bitstream.

[0172] The present disclosure is not limited to include all samples adjacent to left border and the top border of the block in the LIC parameter calculation and may include only a subset of the samples in some embodiments. LIC is described for inter prediction in the Enhanced Compression Model (ECM) software algorithm that is currently under coordinated exploration study by the Joint Video Exploration Team (JVET) of ITU-T Video Coding Experts Group (VCEG) and ISO / IEC MPEG as potential enhanced video coding technology beyond the capabilities of VVC. Although the present disclosure describes LIC for inter prediction, many of the described embodiments are equally applicable to intra prediction in which prediction blocks for a current block are generated from reference blocks obtained from the same picture as that of the current block.

[0173] Illumination variations in reference blocks sometimes yield large prediction errors. LIC was proposed to improve inter prediction when such illumination variation exists in the reference block. Further improvement in addressing illumination variations in the reference block may be obtained by, instead of the one-tap filter in LIC, using a multiple-tap filter for illumination compensation so that correlations between multiple template samples can beDocket No.: 23-2054PCT captured and addressed by the use of the filter. Further, in some examples, complex non-linear filter models and / or non-linear functions applied to components of linear filter models may be used to generate prediction blocks that better compensate for illumination variations between reference blocks and corresponding current blocks.

[0174] In some embodiments, a plurality of filter models (e.g., which may include one or more multi-parameter filter models) are provided from which one filter model may be selected for LIC in inter prediction. Addition of multiple possible filter models increases flexibility at the encoder and enables an appropriate filter model to be selected to cater for different characteristics of content in video blocks. In some examples, the decoder may receive an indication of a filter model of the plurality of filter models, as determined and signaled by the encoder, to be used for LIC in inter prediction. In other examples, the encoder and decoder may reciprocally (e.g., independently and identically) derive that filter model from the plurality of filter models such that no signaling of that filter model is needed in the bitstream.

[0175] Example embodiments may provide for changing the size and / or shape of the filter for sampling the templates, and / or for changing the size of the templates to adapt the illumination compensation in accordance with the current block’s block size / shape and / or content. The multiple-tap filter may provide for improving capturing of correlations among neighboring template samples improving the accuracy of the illumination compensation model compared to the one-tap filter in LIC. Moreover, templates of heights greater than one can be used to obtain more template samples and thereby further improve the accuracy of the illumination compensation model.

[0176] FIG.18A shows an example of a method 1800 for generating (e.g., calculating) a prediction block by using an illumination compensation function (e.g., a filter model) that uses a multiple-tap filter (e.g., multi-parametric reference filter (MPRF)) to sample the current template and the reference template, according to some embodiments. The method 1800 can be performed by an encoder, for example, encoder 200 shown in FIG.2, and / or a decoder, for example, decoder 300 shown in FIG.3. At the encoder, the current block may be subtracted from the prediction block to obtain the prediction error (e.g., a residual or a residual block) that is then encoded into a bitstream. At the decoder the prediction error received in a bitstream may be added to the prediction block to obtain the current (reconstructed) block.

[0177] At operation 1802, template samples from a reference template are obtained using a multiple-tap filter model. FIG.18B illustrates an example reference template 1814 and example multiple-tap filter models 1818, 1820, and 1822 that can be used on the reference template 1814 to obtain a plurality of reference template samples for each sample location in the reference template. Corresponding current template samples are obtained for each sample location in the current template. As in conventional LIC technologies, the reference template 1814 extends over the left edge and the top edge of the boundary 1812 of the reference block 1810. In some examples, the reference template and the current template have identical size, shape and relative placement relative to their respective blocks.

[0178] In contrast to conventional LIC, the templates (the current template and the reference template) in example embodiments may have a height greater than 1 sample. For example, template 1814 may have a height of 3 (3 samples). Additionally, in contrast to the one-tap filter used in conventional LIC, example embodiments use aDocket No.: 23-2054PCT multiple-tap filter model such as, for example, one of multiple-tap filter models 1818-1822. The cross-shaped 5-tap filter model 1818 and the x-cross shaped 5-tap filter model 1820 each obtains 5 samples (e.g., a target sample and four neighboring / adjacent samples) at each template sample location in the template. The 3x3 square-shaped 9-tap filter model 1822 obtains 9 samples (e.g., a target sample and all neighboring / adjacent samples) at each template sample position. The example filter models 1818-1822 each illustrates an arrangement of a plurality of spatial components adjacent to a center spatial component C (which may correspond to a template sample location). In the illustrations in FIG.18B, each filter spatial component is indicated relative to the center spatial component C as north N, north east NE, east E, south east SE, south S, south west SW, west W, or north west NW. Each filter shape and size may yield different illumination compensation results when applied to a reference block, based on the suitability of the filter’s size and shape to capture the block’s image characteristics.

[0179] Due to the size and shape of the multiple-tap filters such as, for example, provided by filter models 1818- 1822, the template samples obtained by the multiple-tap filter may include some samples that are immediately adjacent to the template. FIG.18B illustrates outer samples 1816 some of which may be obtained as template samples when any of the multiple-tap filter models 1818-1822 are used on template 1814. For example, in the illustration shown in FIG.18B, spatial component C of filter model 1818 is positioned within the template 1814 such that spatial components N and W of filter model 1818 may be outside of template 1814 and overlay outer samples 1816. The illustrated position of filter model 1820 within template 1814 results in the filter model 1820 overlapping 3 outer samples 1816. The illustrated position of filter model 1822 within template 1814 results in the filter model 1822 overlaying 5 outer samples 1816.

[0180] Returning to method 1800, at operation 1804, the template samples (neighbor samples of the current block and the reference block) obtained at operation 1802, are used to calculate multiple spatial parameters (e.g., coefficients of the filter model). For example, in some embodiments, a respective spatial parameter is calculated for each tap in the applied filter. When, for example, 5-tap filter model 1818 is the filter that is used on the reference template, 5 spatial parameters are calculated, and when the 9-tap filter model 1822 is the filter model that is used on the reference template, 9 spatial parameters are calculated. The spatial parameter for a particular filter tap spatial component can be calculated by aggregating template samples corresponding to that filter tap spatial component according to an equation such as, for example, equation (20). The calculation of spatial parameters for the multiple- tap filter model may be thought of as similar to the calculation of the scale parameter for the one-tap filter as shown in equation (20).

[0181] An offset parameter (also referred to as a bias term or a bias component) can be calculated based on one or more aspects of the blocks and / or the calculated spatial parameters. For example, in some embodiments the offset is calculated based on the calculated spatial parameters by using an equation such as equation (21) adapted for the multiple-tap filter model.

[0182] At operation 1806, the set of coefficients (the plurality of spatial parameters) and the offset parameter calculated at operation 1804 are applied to respective reference samples to obtain respective predicted samples ofDocket No.: 23-2054PCT the prediction block. This operation may be referred to as applying the multiple-tap filter corresponding to the multiple- tap filter model being applied to the reference block.

[0183] The calculation of the respective samples of the prediction block can be done in accordance with an equation that convolves the respective coefficients in the calculated set of coefficients with reference samples. An example equation for convolving the set of coefficients and a reference sample to obtain a predicted sample is as follows:offset. (22)

[0184] Here, {a&, bL, cO , dJ} is the set of coefficients, f (⋅), f^(⋅), f^(⋅) are non-linear functions, r(x, y) arereference samples, r′(x, y) are gradients (derivatives) of reference samples, and r′′(x, y) are second-orderderivatives of reference samples. Equation 22 shows an example manner in which a set of 4 calculated coefficients is convolved with reference samples to obtain predicted samples. Each of the coefficients a&, bL, cO, dJ may be obtainedin a manner similar to the obtaining of the scale parameter described in relation to equation (20) by using a collection of template samples (current template samples and reference template samples). An example manner in which coefficients a&, bL, cO, cJ may be determined is described below.

[0185] When using equation (22) to determine coefficients a&, bL, cO , dJ, the r(x,y) is a reference template sampleand p(x,y) is a current template sample. The first term ∑air(x,y) comprises N, E, S, W, and C samples. ∑air(x,y) can be expanded, e.g., as:∑a&r(x, y) = a r(x, y − 1) + a^r(x + 1, y) + a^r(x, y + 1) +a0r(x − 1, y) + aUr(x, y) (23)

[0186] In equation (23), the template samples corresponding to N, E, S, W, and C spatial components of the 5-tap filter model 1818 are denoted as r(x,y-1), r(x+1,y), r(x,y+1), r(x-1,y), and r(x, y), respectively. For the following terms comprising ‘b’, ‘c’ and ‘d’ coefficients, these coefficients are applied to some non-linear functions of the N, E, S, W, and C samples (second term ∑bLf (r(x, y) ), non-linear functions of gradients of the samples (third term∑cOf^MrP(x, y)N) and non-linear functions of second-order derivatives of the samples (fourth term∑dJ f^ MrPP(x, y)N).

[0187] f() could be applied to a set of gradient values {rP^ (x, y), rP! (x, y), rP^! (x, y)}. One of the examples of asuch a non-linear function:f(x, y) = √(rP^ (x, y)^ + (rP! (x, y)^

[0188] Another example of such a non-linear function is a clipping function defined for some threshold value T:f(x, y) = min (0, max (T, rP(x, y))orf(x, y) = min (0, max (T, rPP(x, y)).Docket No.: 23-2054PCT

[0189] Threshold value T could be selected from the reference area samples, e.g., by taking a mean value in the reference area. Another example is a square function, defined, e.g., as f(x, y) = rP (x, y)^ or f(x, y) P ( )^^ = r! x, y .Another example is a maximum of squares function: f(x, y) = max (rP^ (x, y)^, rP! (x, y)^.

[0190] Derivation of the coefficients in presence of the non-linear terms may be performed in a similar way as it is done for the linear terms. Specifically, a system of linear equations may be composed and further solved, e.g., using the well-known Gaussian elimination technique. Hence, though operations that are applied to the reference template samples could be non-linear, the filter itself may be linear because its coefficients are fixed after they are determined and do not depend on the reference block samples.

[0191] FIGS.19A and 19B show another manner of performing illumination compensation using a multiple-tap filter, according to some embodiments. In the embodiments illustrated in FIGS.19A and 19B, in addition to the template samples of the multiple-tap filters, their gradients are used as inputs to the process of coefficient calculation.

[0192] FIG.19A shows an example method 1900 of using the gradients of multiple-tap filter samples to obtain illumination compensated predicted samples for inter prediction, according to some embodiments. The method 1900 can be performed by an encoder, for example, encoder 200 shown in FIG.2, and / or a decoder, for example, decoder 300 shown in FIG.3. At the encoder, the current block may be subtracted from the prediction block to obtain the prediction error that is then encoded into a bitstream. At the decoder the prediction error received in a bitstream may be added to the prediction block to obtain the current (reconstructed) block.

[0193] At operation 1902, in the same manner as described above in relation to operation 1802, template samples are obtained from a current template and from a reference template. The reference template samples are obtained by applying a multiple-tap filter model such as, for example, any one of the filter models 1818-1822, to the reference template.

[0194] At operation 1904, gradients (e.g., first-order derivatives, second-order derivatives, etc.) of the samples are calculated. In FIG.19B, illustrated filter models 1912, 1914 and 1916 graphically show how first-order derivatives are obtained from the samples of filter models 1818, 1820, and 1822, respectively. An example of a second-order derivative of filter model samples is shown in the 17-tap filter model 1918. As graphically represented in the filter model illustrations 1912-1916, the first-order derivative represents changes in pairs of samples, and, as shown in 1918, the second-order derivative represents changes in respective pairs of pairs of samples. The first-order derivatives can capture information associated with edges in the pictures, and the second-order derivatives can capture information associated with smoothness of such edges. In example embodiments, the template samples only, or the template samples and their derivative(s) can be used as inputs to the next operation. Respective embodiments may use first-order derivatives and / or a higher-order derivative (e.g., second-order derivative or higher).

[0195] At operation 1906, the set of template samples obtained at operation 1902 and one or more sets of derivative values (e.g., first-order and / or higher-order) calculated from the template samples obtained at operation 1904, are taken as input to calculate the set of coefficients. For example, a respective spatial parameter can be calculated based on template samples, non-linear function(s) of template samples, non-linear functions of derivativesDocket No.: 23-2054PCT of the template samples, or a combination thereof. Equations (23) and (22) above illustrate how the set of coefficients for a multiple-tab filter model can be calculated.

[0196] In some embodiments, an offset parameter can be calculated based on one or more coefficients of the set of calculated coefficients. For example, the offset may be based on calculated coefficients in a manner similar to that shown in equation (21).

[0197] At operation 1908, the calculated set of coefficients and the offset are used to determine the prediction block. The coefficients and the offset can be combined with the reference samples in the manner shown in equation (22). As shown in the equation (22), the value of a predicted sample can be determined by multiplying the respective coefficients by the reference samples, derivatives of the reference sample, and / or non-linear functions of the reference sample and / or its derivative(s).

[0198] FIG.20 shows a flowchart of a method 2000 of signaling the illumination compensation associated with a current block, according to some embodiments. The method may be performed at a decoder, such as, for example, the decoder 300 shown in FIG.3.

[0199] At operation 2002, it is determined whether an indication (e.g., a flag) of illumination compensation is included in the bitstream. If the illumination compensation indication 2004 is present, it may indicate either local illumination compensation (LIC) or illumination compensation based on multi-parametric reference function is applied. In other words, illumination compensation indication 2004 may indicate whether an LIC model or a multi-parameter filter model is to be applied.

[0200] At operation 2006, it is determined whether illumination compensation based on multi-parametric reference function (MPRF) is applied. As used in the present disclosure, MPRF refers to a multi-parameter filter model being used. In some examples, if the illumination compensation based on multi-parametric reference function selection indication (Multi-parameter reference filtering (MPRF) block-level indication) 2008 is set, then illumination compensation based on MPRF is applied. Whether to apply MPRF based illumination compensation (e.g., and if applied, to include the MPRF block-level indication) may be decided based on constraints such as, one or more of block size of the current block, block orientation of the current block, whether uni- or bi- prediction is used for inter prediction, and / or whether affine flag is present, etc. For example, if the block size is too small (e.g., 4x4 etc.) or if the orientation is not conducive for template use, then MPRF illumination compensation may not be used. If bi-prediction is used or if the affine flag is set, then additional improvements provided by MPRF illumination compensation may be considered as unnecessary.

[0201] The MPRF block-level indication 2008 comprises one or more flags indicating aspects of the multiple-tap filter and / or models, such as, for example, 2-parameter model (LIC-like) 6-parameter model, …, 19-parameter model (with gradients and non-linear filter). In some embodiments, the indication 2008 may be an index into a table of respective filter models that can be applied.Docket No.: 23-2054PCT

[0202] FIG.21 shows a method 2100 by which a decoder can determine, when using inter prediction merge mode, whether illumination compensation based on MPRF is to be used for the current block, and if so, what filter model and / or filter model parameters are to be used, according to some embodiments.

[0203] If, at operation 2102, the decoder detects a merge flag indicating merge mode inter prediction, method 2100 proceeds to operation 2106. At operation 2106, the absence or presence of the illumination compensation indication / flag (e.g., illumination compensation (IC) indication 2004) and the presence or absence of a MPRF model indication (e.g., MPRF block level indication at operation 2006) can be inferred based on the corresponding aspects in the selected merge candidate. For example, if a MPRF block-level indication at operation 2006 was received for the selected merge candidate, it can be decided that an MPRF block-level indication at operation 2006 would have been signaled in association with the current block, and, if a particular MPRF model indication was received in association with the selected merge candidate, it can be decided that the same MPRF model indication would be signaled in association with the current block.

[0204] At operation 2106, after inferring the MPRF model indication (e.g., determining a filter model that applies for MPRF), the corresponding model parameters for the current block may either be calculated or may be copied from the selected merge candidate. For example, in one embodiment, the inferred model indication identifies a particular multiple-tap filter model (e.g., any one of filter models 1818-1822), and then, the decoder calculates the set of coefficients based on the templates and the identified filter model to determine the filters (i.e., the multi-tap filter model with the calculated coefficients / parameters). In another embodiment, the inferred model indication identifies a particular multiple-tap filter model (e.g., any one of filter models 1818-1822), and the decoder copies the set of coefficients (e.g., also referred to as parameters of the filter model) from the selected merge candidate as the set of coefficients for the current block. Accordingly, the multiple-tap filter model and its coefficients may be derived (e.g., inferred by copying) to determine the multiple-tap filter, which corresponds to the selected multiple-tap filter model with the derived coefficients.

[0205] In some embodiment, the model indication may be encoded so that the length of the model indication as represented in the bitstream is proportional to the number of parameters (e.g., coefficients of spatial components) in the filter model (e.g., increases / decreases as the number of model parameters for the model increases / decreases). FIG.22 shows an example coding scheme (e.g., a unary code) in which the unary codes 1, 01, 0…01, 0…001 are used to represent filter models such as a 2-paremeter model, a 3-parameter model, a 12-parameter model, and a 19- parameter model, respectively. This enables taking advantage of the characteristic that the probability of models with higher number of parameters being necessary decreases with the increase of the number of parameters.

[0206] In some examples, the maximum number of model parameters may depend on the size of the prediction block and / or the aspect ratio of the prediction block. In some examples, the encoder and decoder may reciprocally determine (e.g., select) the available / permitted filter models to be indicated by codewords of the coding scheme. For example, the encoder and decoder may reciprocally determine that, e.g., the codeword 1 refers to a 2-parameterDocket No.: 23-2054PCT model and the codeword 01 refers to a 4-parameter model based on a 3-parameter model determined not to be used / available.

[0207] FIG.23A shows an example flowchart of a method 2300 of determining (e.g., deriving) a filter model to be applied for illumination compensation in inter prediction, according to some embodiments. The method 2300 can be performed by an encoder, for example, encoder 200 shown in FIG.2, and / or a decoder, for example, decoder 300 shown in FIG.3.

[0208] At operation 2302, a list of N filter models (e.g., a first plurality of filter models) that can be used for illumination compensation of a reference block for a current block is determined. The N filter models may be a subset of a plurality of filter models (e.g., a second plurality of filter models) that are available (e.g., defined or enabled) for inter prediction in the system. For example, the subset of N filter models can be selected based on the block size. N is a positive integer greater than 1.

[0209] At operation 2304, for each of the N filter models in the subset, the filter parameters (e.g., model coefficients) are derived using a current template of the current block and a refence template of the reference block. The model coefficients can be derived, for example, as described in relation to equations (23) and (22) above. In some examples, the model coefficients for each filter model is derived based on a first portion of the current template and a first portion of the reference template. In some examples, the first portion of the current template and the first portion of the reference template may have the same shape, size, and orientation. Further, the first portion of the current template and the first portion of the reference template may have the same relative position within respect to the current template and the reference template, respectively.

[0210] FIG.23B shows an example reference template format and a current template format that are used to derive the filter model, of a plurality of filter models, in the method shown in the flowchart of FIG.23A, according to some embodiments. FIG.23B shows a reference block 2320 and an associated reference template and a current block 2330 and an associated current template. In contrast to the reference template 1814 described in relation to FIG. 18B, the reference template of the reference block 2320 has a first template portion 2323 that can be used for deriving parameters for the filter model comparison and a second portion (probe areas 2325), referred to herein as a probe template, that can be used to compare error estimations of the different models. The probe template may be formed by the neighboring row and column that is closest to the reference block boundary 2322. As illustrated, multiple-tap filters (e.g., any of the illustrated 3x3 square filter, the cross-shape filter, the x-cross filter, etc.) can be applied to template portion 2323 without having the filters overlap the probe template. Outer template samples 2326 that are adjacent to template portion 2323 may be included within the filter coverage area of the reference template. When deriving the model coefficients for a particular reference filter model, the corresponding reference filter is applied to the reference block template portion 2323 of the reference template. A current block 2330 with its current template is also illustrated. In the current template, a first portion 2333 of the template is used to derive parameters for the model comparison, and a second portion, that is the probe area 2335 and also referred to as probe template, that is used to compare error estimations of different filter models. According to some embodiments, the modelDocket No.: 23-2054PCT coefficients are determined by using template samples obtained from the template portion 2323 in the reference template (e.g., using a multiple-tap filter model) and template portion 2333 in the current template.

[0211] Returning to method 2300, at operation 2306, each of the N filters, using the calculated model coefficients for each filter model, are applied to the current template and the reference template to calculate prediction errors for each of the N filter models. In some examples, each filter, corresponding to a respective filter model with determined / derived model coefficients, may be applied to a second portion of the current template and a second portion of the reference template. In some examples, the second portion of the current template and the second portion of the reference template may have the same shape, size, and orientation. Further, the second portion of the current template and the second portion of the reference template may have the same relative position within respect to the current template and the reference template, respectively. In some examples, the first and second portions of the current template do not overlap and the first and second portions of the reference template do not overlap. For example, each filter may be applied to a second portion of the reference template such as probe areas 2325 in the reference template and the resulting / calculated predicted sample (e.g., that is an illumination compensated sample value) is compared to the sample in the corresponding template area 2335 associated with the current block, to calculate the prediction error.

[0212] At operation 2308, the errors calculated for the respective filter models are compared, and the filter model that provides the minimal error (e.g., as applied to the second portion of the reference template and compared to the second portion of the current template, which is also referred to as the probe templates) may be selected as the filter model to apply to the reference block. In some embodiments, criteria other than the minimum error can be used in addition to, or in place of, the minimum error, in selecting the filter model to be applied to the reference block.

[0213] At operation 2310, the filter corresponding to the selected filter model is applied to the reference block to generate the predictor for the current block. For example, the predictor may be calculated using an equation such as equation (22) with r(x,y) being reference samples and p(x,y) being prediction samples. Note that the filter would already have its set of coefficients determined at 2304 by using an equation such as equation (23) with r(x,y) being reference template samples and p(x,y) being current template samples.

[0214] It should be noted that the plurality of filter models considered at operation 2302 may include various sizes of filter models.

[0215] FIG.24 illustrates an example of when filter model parameters can be obtained from a merge candidate, according to some embodiments. Examples of merge mode and indications of merge candidates are described above with respect to FIG.15A and FIG.15B. As described above with respect to FIG.21, in merge mode inter prediction, the MPRF filter model information can either be signaled in the bitstream or can be inferred at the decoder. For example, the determination of which multiple-tap filter model to use for the current block may either be signaled in the bitstream or may be based on an indication copied from the selected merge candidate. Moreover, the model parameters to be used with the filter model may either be signaled in the bitstream or may be based on an indication copied from the selected merge candidate.Docket No.: 23-2054PCT

[0216] In some embodiments, for example, after having determined based on the selected merge candidate that a particular MPRF multiple-tap filter model applies to the current block, the decoder determines the model parameters in accordance with a block size of the selected merge candidate. For example, when the current block (corresponding to PU0) 2402 is being decoded in merge mode inter prediction, the selected merge candidate may be signaled as candidate 12404, e.g., a neighboring block containing a sample / pixel at the location shown in FIG.24. The decoder determines that the block size of the block 2406 corresponding to the sample of candidate 12404 (the signaled selected merge candidate) is larger than the block size of current block 2402, and, since the larger size of block 2406 is likely indicative of blocks 2406 and 2402 being parts of the same object, may copy the model parameters corresponding to the multiple-tap filter model from selected merge candidate block 2406.

[0217] FIG.25A and FIG.25B show example block sizes of merge candidate blocks that can be considered when deciding whether to obtain filter model parameters from one of the merge candidates, according to some embodiments. As shown, the block size of the block of merge candidate 1 is larger than the block size of PU0 which may be a current block to be coded, and the block size of the block of merge candidate 3 is smaller than the block size of PU0. Therefore, when the selected merge candidate is determined to be merge candidate 1, the model parameters may be directly copied (e.g., inferred or inherited) from the selected merge candidate, and, when the selected merge candidate is determined to be merge candidate 3, the model parameters can be derived. Examples for determining or deriving the model parameters (e.g., coefficients of components of the filter model) are described above with respect to FIGS.17-19. In example embodiments, the size difference of a merge candidate block and the current block may be determined in accordance with the configured threshold. Further, the decoder may determine whether to copy (i.e., infer or inherit) the coefficients of the filter model (copied or derived from the indicated merge candidate) or to separately derive those coefficients. In some embodiments, the encoder and the decoder reciprocally (e.g., independently and identically) determine whether model parameters (e.g., coefficients) of a filter model, associated with an indicated merge candidate, are to be copied or derived.

[0218] FIG.26 shows a flowchart 2600 of a method for applying illumination compensation using MPRF in inter prediction, according to some embodiments. The method of flowchart 2600 may be implemented by an encoder, such as encoder 200 in FIG.2.

[0219] The method of flowchart 2600 begins at 2602. At 2602, the encoder determines, based on illumination compensation being enabled for a reference block, a multiple-tap filter model to be applied to the reference block to generate a prediction block for coding a current block.

[0220] In some embodiments, the determining may include using a preconfigured (or default) multiple-tap filter model. For example, in some embodiments, any one of the filter models 1818-1822 may be determined as the filter model for which the corresponding filter is applied to the reference block.

[0221] In some embodiments, the determining may include selecting one filter model, from among a plurality of filter models, as the filter model for which the corresponding filter is applied to the reference block. An example method of selecting a filter model is described in relation to FIGS.23A and 23B.Docket No.: 23-2054PCT

[0222] The determination as to whether illumination compensation is enabled may be based on configuration (e.g., setting specifying illumination compensation to be always enabled for inter prediction), or considerations based on one or more of a current block size, current block orientation, whether uni- or bi- prediction is used in the inter prediction, or whether an affine flag is associated with the current block.

[0223] As noted above, in some embodiments, the multiple-tap filter model is determined from a plurality of filter models. The plurality of filter models may comprise the multiple-tap filter model and a linear filter model with a single spatial component and a bias term (e.g., a bias component in the linear filter model).

[0224] At operation 2604, the encoder determines a plurality of coefficients of the multiple-tap filter model, based on: a first plurality of template samples of a current template of the current block in a current picture; and a second plurality of template samples of a reference template of the reference block in a reference picture different from the current picture.

[0225] The first plurality of template samples is obtained from the current template associated with the current block the current picture. The second plurality of template samples is obtained from the reference template of the reference block from a reference picture. The current template is adjacent to a current block in the current picture and the reference template is adjacent to a reference block in the reference picture. The current template comprises a plurality of columns of samples nearest a left edge of the current block and a plurality of rows of samples nearest a top edge of the current block, and the reference template comprises a plurality of columns of samples nearest a left edge of the reference block and a plurality of rows of samples nearest a top edge of the reference block. As would be noted, in inter prediction the current picture and the reference picture are respective pictures in a sequence of pictures. The second plurality of template samples is obtained by using the determined / selected multiple-tap filter model to the reference template.

[0226] In some embodiments, the second plurality of template samples comprises some samples adjacent to the reference template. In some embodiments, the samples adjacent to the reference template comprise padded samples obtained by copying the corresponding template sample values. In some embodiments, the outer samples include real sample (e.g., neighbor block sample that is a reconstructed sample) values. Padded samples may provide some savings in memory bandwidth. FIG, 18B shows an example reference template 1814 according to embodiments of this disclosure. The figure also shows outer samples 1816 adjacent to the reference template 1814.

[0227] In some embodiments, the multiple-tap filter model comprises a plurality of spatial components comprising: one spatial component for a target sample on which the multiple-tap filter is applied, and a spatial component for each selected sample adjacent to the target sample. For example, in the 5-tap filter model 1818, when the spatial component for a target sample on which the multiple-tap filter is applied is C, the spatial components N, S, E, W correspond to the selected samples adjacent to the target sample. FIG.18B shows a selection of example non- limiting multiple-tap filter models. As illustrated, in respective embodiments, the multiple-tap filter model may have 2 or more template samples arranged in a plurality of ways. In some embodiments, the multiple-tap filter model comprises 5 spatial components, 9 spatial components, 17 spatial components, or another number of spatialDocket No.: 23-2054PCT components. In respective embodiments, the multiple-tap filter model comprises a plurality of spatial components arranged in a cross shape, in a x-cross shape, in a rectangular shape, or another shape.

[0228] The encoder determines the plurality of coefficients of the illumination compensation function, based on the first plurality of template samples and the second plurality of template samples. For example, for illumination compensation using MPRF, the spatial parameters (e.g., set of coefficients with a function similar to the scale parameter used in equation (20)) and the offset parameter may be determined. The spatial parameters may comprise a plurality of spatial parameters (coefficients).

[0229] Example calculation of the spatial parameters and the offset parameter are described above in relation to equations (23) and (22) for a selected multiple-tap filter model. It would be understood that the parameters for other multiple-tap filter models can be determined in a similar manner. As noted above, in example embodiments, the spatial parameters may be determined based on reference template samples, derivatives of reference template samples, and / or non-linear functions of reference samples or their derivatives.

[0230] The determining of the plurality of coefficients may be based on a difference minimization technique applied between the first plurality of template samples and a plurality of filtered samples output from the multiple-tap filter model applied to the second plurality of template samples. For example, such difference minimization techniques may include minimum squared error, SAD, SATD, SSD, etc.

[0231] In some embodiments, the multiple-tap filter model comprises two or more spatial components and a bias component. The multiple-tap filter model may comprise a linear filter model, a linear filter model comprising one or more components with a non-linear function, a derivative filter model of an nth order, wherein n is n is a positive integer (e.g., first order, second order, etc.), or a combination of linear filter models. (e.g., a first order model and a second order model).

[0232] At operation 2606, the encoder applies a multiple-tap filter, corresponding to the multiple-tap filter model with the determined plurality of coefficients, to the reference block to generate the prediction block. The multiple-tap filter may be an example of the illumination compensation function and may include a plurality of components comprising the determined plurality of coefficients and a bias term (e.g., a bias component). Equation (22) may be used in calculating the predicted samples based on the spatial parameters calculated using reference template and the current template, and using reference block samples.

[0233] In some embodiments, the applying includes calculating each predicted sample of the prediction block based at least on the determined plurality of coefficients, a reference sample, and the bias term, wherein the reference sample is from the reference block. In some embodiments the applying includes calculating each predicted sample of the prediction block based at least on the determined set of coefficients, a reference sample, one or more non-linear functions of the reference sample, and the bias term, wherein the reference sample is from the reference block. The one or more non-linear functions of the reference sample may comprise at least a first-order derivative of the reference sample or a second-order derivative of the reference sample.Docket No.: 23-2054PCT

[0234] At operation 2608, the encoder encodes, in a bitstream, a prediction error based on the prediction block and the current block. The encoded prediction error values, when illumination compensation using MPRF has been applied to the reference block, may be smaller compared to when such illumination compensation is not applied, and thus may be more efficiently encoded.

[0235] According to some embodiments, operations of flowchart 2600 may further include the encoder directly signaling whether or not illumination compensation using MPRF is being applied to the current block. For example, the encoder may encode a first indication indicating that an illumination compensation function is applied and a second indication indicating one or more aspects of the illumination compensation function and / or the multiple-tap filter. The encoding of the second indication indicating one or more aspects of the illumination compensation function and / or the multiple-tap filter may include dynamically deciding whether to apply the illumination compensation function and / or the multiple-tap filter to the reference block. The decision may be made based on factors such as, for example, the block size and / or block orientation of the current block, whether uni- or bi- prediction is used, the affine flag, etc. When included, the second indication may include an identification of the multiple-tap filter and / or a parametric model of the illumination compensation function. For example, the second indication may identify which one of parametric models from a predetermined set of models such as, for example, a 2-parameter model (LIC-like), 6-parameter model, …, and 19-parameter model (with gradients and non-linear filter), is being used. The second indication may be encoded efficiently using a codeword where a relative length of the codeword is determined in accordance with a relative number of parameters in the parametric model. An example unary code is shown in FIG.22.

[0236] According to some embodiments, operations of flowchart 2600 may further include dynamically switching between a first mode in which a local illumination compensation (LIC) is applied to the reference block and one or more second modes in which illumination compensation based on the multiple-tap filter (MPRF enabled) is applied to the reference block. For example, when at operation 2006 described above, it is determined not to perform illumination compensation using MPRF, instead LIC-like illumination compensation (e.g., a 1-tap filter as in conventional LIC, but with templates of height more than 1) can be performed and the local illumination indication that is signaled can indicate to the decoder that the LIC-like illumination compensation (e.g., without a multiple-tap filter) is being used.

[0237] In some embodiments, when inter prediction merge mode is used for the current block, the encoder may not include the first indication and / or the second indication in the bitstream, and the decoder may infer the first indication and the second indication from the selected merge candidate.

[0238] FIG.27 shows a flowchart of a method 2700 for determining a current block that has been encoded by applying illumination compensation using MPRF in inter prediction, according to some embodiments. The method 2700 may be implemented by a decoder, such as decoder 300 in FIG.3.

[0239] The method 2700 begins at 2702. At 2702, the decoder receives, in a bitstream, a prediction error associated with a current block.Docket No.: 23-2054PCT

[0240] At operation 2704, the decoder determines, based on illumination compensation being enabled for a reference block, a multiple-tap filter model to be applied to the reference block to generate a prediction block for reconstructing the current block.

[0241] In some embodiments, the determining may include receiving one or more indications in the bitstream indicating an MPRF filter / filter model or using a preconfigured (or default) multiple-tap filter model. For example, in some embodiments, any one of the filter models 1818-1822 may be signaled or determined as the filter model for which the corresponding filter is applied to the reference block.

[0242] In some embodiments, the determining may include selecting one filter model, from among a plurality of filter models, as the filter model for which the corresponding filter is applied to the reference block. An example method of selecting a filter model is described in relation to FIGS.23A and 23B.

[0243] The determination as to whether illumination compensation is enabled may be based on configuration (e.g., setting specifying illumination compensation to be always enabled for inter prediction), or considerations based on one or more of a current block size, current block orientation, whether uni- or bi- prediction is used in the inter prediction, or whether an affine flag is associated with the current block.

[0244] At operation 2706, the decoder determines a plurality of coefficients of the multiple-tap filter model, based on: a first plurality of template samples of a current template of the current block in a current picture; and a second plurality of template samples of a reference template of the reference block in a reference picture different from the current picture.

[0245] The first plurality of template samples is obtained from the current template associated with the current block the current picture. The second plurality of template samples is obtained from the reference template of the reference block from a reference picture. The current template is adjacent to a current block in the current picture and the reference template is adjacent to a reference block in the reference picture. The current template comprises a plurality of columns of samples nearest a left edge of the current block and a plurality of rows of samples nearest a top edge of the current block, and the reference template comprises a plurality of columns of samples nearest a left edge of the reference block and a plurality of rows of samples nearest a top edge of the reference block. As would be noted, in inter prediction the current picture and the reference picture are respective pictures in a sequence of pictures. The second plurality of template samples is obtained by using the determined / selected multiple-tap filter model to the reference template.

[0246] In some embodiments, the second plurality of template samples comprises some samples adjacent to the reference template. In some embodiments, the samples adjacent to the reference template comprise padded samples obtained by copying the corresponding template sample values. In some embodiments, the outer samples include real sample (e.g., neighbor block sample that is a reconstructed sample) values. Padded samples may provide some savings in memory bandwidth. FIG, 18B shows an example reference template 1814 according to embodiments of this disclosure. The figure also shows outer samples 1816 adjacent to the reference template 1814.Docket No.: 23-2054PCT

[0247] In some embodiments, the multiple-tap filter model comprises a plurality of spatial components comprising: one spatial component for a target sample on which the multiple-tap filter is applied, and a spatial component for each selected sample adjacent to the target sample. For example, in the 5-tap filter model 1818, when the spatial component for a target sample on which the multiple-tap filter is applied is C, the spatial components N, S, E, W correspond to the selected samples adjacent to the target sample. FIG.18B shows a selection of example non- limiting multiple-tap filter models. As illustrated, in respective embodiments, the multiple-tap filter model may have 2 or more template samples arranged in a plurality of ways. In some embodiments, the multiple-tap filter model comprises 5 spatial components, 9 spatial components, 17 spatial components, or another number of spatial components. In respective embodiments, the multiple-tap filter model comprises a plurality of spatial components arranged in a cross shape, in a x-cross shape, in a rectangular shape, or another shape.

[0248] The decoder determines the plurality of coefficients of the illumination compensation function, based on the first plurality of template samples and the second plurality of template samples. For example, for illumination compensation using MPRF, the spatial parameters (e.g., set of coefficients with a function similar to the scale parameter used in equation (20)) and the offset parameter may be determined. The spatial parameters may comprise a plurality of spatial parameters (coefficients).

[0249] Example calculation of the spatial parameters and the offset parameter are described above in relation to equations (23) and (22) for a selected multiple-tap filter model. It would be understood that the parameters for other multiple-tap filter models can be determined in a similar manner. As noted above, in example embodiments, the spatial parameters may be determined based on reference template samples, derivatives of reference template samples, and / or non-linear functions of reference samples or their derivatives.

[0250] The determining of the plurality of coefficients may be based on a difference minimization technique applied between the first plurality of template samples and a plurality of filtered samples output from the multiple-tap filter model applied to the second plurality of template samples. For example, such difference minimization techniques may include minimum squared error, SAD, SATD, SSD, etc.

[0251] In some embodiments, the multiple-tap filter model comprises two or more spatial components and a bias component. The multiple-tap filter model may comprise a linear filter model, a linear filter model comprising one or more components with a non-linear function, a derivative filter model of an nth order, wherein n is n is a positive integer (e.g., first order, second order, etc.), or a combination of linear filter models. (e.g., a first order model and a second order model).

[0252] In some embodiments, the determining a multiple-tap filter model may comprise determining, based on at least relative block sizes of the selected merge candidate block and a current block, the multiple-tap filter model. For example, as described above in relation to FIG.24 (also FIGS.25A-25B), when merge mode inter prediction is used, the filter model for the current block may be inferred from the filter model of the selected merge candidate. The inferring of the filter model from the selected merge candidate may be performed for any selected merge candidates, or only when the block size of the selected merge candidate is larger (e.g., beyond a threshold) than that of theDocket No.: 23-2054PCT current block. Moreover, when the filter model is inferred from the selected merge candidate, the filter model coefficients may either be determined based on the templates, or may be inferred from the selected merge candidate (without calculating based on the templates of the current block and the reference block).

[0253] At operation 2708, the decoder applies a multiple-tap filter, corresponding to the multiple-tap filter model with the determined plurality of coefficients, to the reference block to generate the prediction block. The multiple-tap filter may be an example of the illumination compensation function and may include a plurality of components comprising the determined plurality of coefficients and a bias term (e.g., a bias component). Equation (22) may be used in calculating the predicted samples based on the spatial parameters calculated using reference template and the current template, and using reference block samples.

[0254] In some embodiments, the applying includes calculating each predicted sample of the prediction block based at least on the determined plurality of coefficients, a reference sample, and the bias term, wherein the reference sample is from the reference block. In some embodiments the applying includes calculating each predicted sample of the prediction block based at least on the determined set of coefficients, a reference sample, one or more non-linear functions of the reference sample, and the bias term, wherein the reference sample is from the reference block. The one or more non-linear functions of the reference sample may comprise at least a first-order derivative of the reference sample or a second-order derivative of the reference sample.

[0255] At operation 2710, the decoder reconstructs the current block based on the prediction error and the prediction block.

[0256] The operation 2710 may include decoding, from the bitstream, a first indication indicating that the illumination compensation function is to be applied and a second indication indicating one or more aspects of the illumination compensation function and / or the multiple-tap filter. The one or more aspects of the illumination compensation function and / or the multiple-tap filter includes an identification of the multiple-tap filter / filter model and / or a parametric model (e.g., set of parameters) of the illumination compensation function. The identification of the multiple-tap filter and / or the parametric model is encoded in a codeword wherein a relative length of the codeword is determined in accordance with a relative number of parameters in the parametric model. As described above in relation to flowchart 2600, the encoding of the second indication indicating one or more aspects of the illumination compensation function and / or the multiple-tap filter may include the encoder dynamically deciding whether to apply the illumination compensation function and / or the multiple-tap filter to the reference block. The decision may be made based on factors such as, for example, the block size and / or block orientation of the current block, whether uni- or bi- prediction is used, the affine flag, etc. When included, the second indication may include an identification of the multiple-tap filter / filter model and / or a parametric model of the illumination compensation function. For example, the second indication may identify which one of parametric models from a predetermined set of models such as, for example, a 2-parameter model (LIC-like), 6-parameter model, …, and 19-parameter model (with gradients and non- linear filter), is being used. The second indication may be encoded efficiently using a codeword where a relativeDocket No.: 23-2054PCT length of the codeword is determined in accordance with a relative number of parameters in the parametric model. An example unary code is shown in FIG.22.

[0257] In some embodiments, as described above in relation to FIG.21 when merge mode inter prediction applies to the current block, the first indication and the second indication are inferred from the selected merge candidate.

[0258] In existing implementations, LIC reference filtering has been enhanced using a multi-model technique in which reference samples (e.g., in a reference template) neighboring a reference block used to predict a current block are classified into two or more groups according to intensity values of the reference samples and corresponding samples (e.g., in a current sample) neighboring the current block. For example, referring to FIG.17A, a threshold may be applied to samples of reference template 1716 to classify them into a first and a second group. Based on the classified reference samples and corresponding samples of current template 1714, LIC parameters may be derived for each of the first and second groups to determine a first LIC filter and a second LIC filter, respectively. Reference block samples of reference block 1708 may be similarly classified into the first and second groups. Then, a prediction block for current block 1704 may be generated from reference block 1708 by applying the first LIC filter (with corresponding derived LIC parameters) to the reference block samples classified in the first group and applying the second LIC filter (with corresponding derived LIC parameters) to the reference block samples classified in the second group.

[0259] By applying multi-model LIC filtering, different LIC parameters may be derived for two groups of classified reference block samples to derive a more accurate prediction block. LIC, however, only compensates for uniform changes in brightness and contrast within a block. However, due to the changes of illumination conditions within a scene captured by video such as when an object is moving relative to light sources and a camera capturing the video, different parts of the object may reflect light differently and results in various features being present in the reference block such as edges, ridges, smooth areas, textures, etc. The illumination changes of these features are not uniform and are not accurately predicted or adjusted by LIC filtering.

[0260] Embodiments of the present disclosure are directed to feature-based classification of reference samples and applying multi-parametric reference filtering to classified samples to generate prediction blocks that accurately compensate reference blocks according to detected features. For example, features that are detected from and used to classify the reference block samples may be based on directionality determined for reference samples of a reference template of a reference block and / or for reference block samples of the reference block. For example, features that are detected from and used to classify the reference block samples may be based on activity levels (e.g., change in intensities) determined for reference samples of the reference template of the reference block and / or for the reference block samples of the reference block. By performing feature-based classification and applying multi- parametric reference filtering, a prediction block (e.g., generated from a filtered reference block) used to predict a current block is more similar to the current block, which leads to smaller prediction errors and corresponding residuals being signaled and obtained from a bitstream. For example, the multi-parametric reference filtering techniquesDocket No.: 23-2054PCT described above with respect to FIGS.18-27 may be applied to each classified group of reference samples to generate a more accurate prediction block for the current block.

[0261] Additionally, by performing feature-based classification, the multi-parametric filters which may be selected to filter for specific feature types may be more accurate and results in the generated prediction block with smaller prediction errors when compared to the current block that it is predicting.

[0262] FIG.28A is a schematic view of an activity classifier 2800 of a coder (e.g., encoder 200, decoder 300), according to some embodiments. As illustrated, in some embodiments, activity classifier 2800 is configured to classify at least some samples in a reference picture (e.g., reference picture 1706). As shown, in some embodiments, activity classifier 2800 classifies reference samples (e.g., luma components of pixels) neighboring a reference block (e.g., reference samples in template 1716 of the reference block 1708, reference samples in template 1814 of the reference block 1810) and / or reference block samples (e.g., luma components of pixels) in the reference block (e.g., samples in the reference block 1708, samples in the reference block 1810) into a plurality of groups (e.g., first group, second group).

[0263] In some examples, activity classifier 2800 may be a type of feature-based classifier in which activity levels of samples in the reference block are determined and used to classify those samples into the plurality of groups. For example, activity classifier 2800 may include a plurality of edge detection filters such as a plurality of Laplacian filters including a first Laplacian filter 2802 and a second Laplacian filter 2804. In this example, first Laplacian filter 2802 may be a vertical Laplacian filter, and second Laplacian filter 2804 may be a horizontal Laplacian filter.

[0264] When the first Laplacian filter 2802 is the vertical Laplacian filter, the first Laplacian filter 2802 is configured to emphasize and detect vertical edges in an image (image including the reference block samples and reference samples in this example). When the second Laplacian filter 2804 is the horizontal Laplacian filter, the second Laplacian filter 2804 is configured to emphasize and detect horizontal edges in the image (image including the reference block samples and reference samples in this example). For example, an output of first Laplacian filter 2802 may indicate how likely the vertical edge is detected with, e.g., higher values indicating vertical edge detection with lower values indicating the vertical edge is likely not detected. Similarly, an output of second Laplacian filter 2804 may indicate how likely the horizontal edge is detected.

[0265] As shown, in some embodiments, the first Laplacian filter 2802 receives the image (image including reference samples and samples from the reference block in this example). In this example, the activity classifier 2800 applies the first Laplacian filter 2802 (vertical Laplacian filter in this example) through convolution with the image. As a result, the first Laplacian filter 2802 determines (e.g., generates) a first filtered image including first filtered samples.

[0266] As shown, in some embodiments, the second Laplacian filter 2804 receives the image (image including reference samples and samples from the reference block in this example). In this example, the activity classifier 2800 applies the second Laplacian filter 2804 (horizontal Laplacian filter in this example) through convolution with the image. As a result, the second Laplacian filter 2804 determines (e.g., generates) a second filtered image including second filtered samples.Docket No.: 23-2054PCT

[0267] As shown, the activity classifier 2800 includes a combiner 2806 (e.g., adder) that is configured to combine the first filtered image and the second filtered image. As a result, the combiner 2806 determines (e.g., generates) a combined image including combined samples. In this example, the combined sample is also referred to as a sum of a first filtered sample from the first Laplacian filter 2802 and a second filtered sample from the second Laplacian filter 2804 corresponding to the first filtered sample.

[0268] In some examples, the plurality of edge detection filters such as first Laplacian filter 2802 and second Laplacian filter 2804 may be applied sample-by-sample to each sample (x,y) from the reference block and / or the reference template to generate a value representing the combination of applying the plurality of edge detection filters to each sample.

[0269] As shown, in some embodiments, activity classifier 2800 includes an activity index indicator 2808 that is configured to indicate an activity index (v) for each sum (combined sample of the first filtered sample and second filtered sample in this example) in the combined value (e.g., combined image). In some embodiments, the activity index indicator 2808 determines the activity index (v) for each combined sample representing the sum of outputs of the plurality of edge detection filters applied to each sample (x,y) as follows: vi= min (15, (1407 × 3 × sum) >> (9 + bitdepth))

[0270] In some embodiments, the “bitdepth” in the code is 8. In some embodiments, the “bitdepth” in the code is 10. In this example, the bitdepth is 10.

[0271] As shown, activity classifier 2800 includes a classifier 2810 that is configured to receive the activity indexes (v) of the sums (of the combined value) from the activity index indicator 2808 and classify each of the sums (combined samples) based on the activity indexes (v) and a lookup table 2812. For example, when an activity index (v) of a sum is 0, the classifier 2810 classifies the sum (sample associated with the sum) into the first group (group 0).

[0272] In some embodiments, the coder classifies the reference samples and / or samples in the reference block into a plurality of groups (first group (group 0), second group (group 1), third group (group 2), fourth group (group 3), and fifth group (group 4) in this example) based on the classification result from the classifier 2810. For example, when the classifier 2810 classifies a first combined sample (first sum) at a first position of the combined image into the first group, the coder determines a first sample at a first position of the image (corresponding to the first position of the combined image) into the first group. When the first position is associated with the one of the reference samples, the coder classifies the one of the reference samples into the first group. When the first position is associated with the one of the samples in the reference block, the coder classifies the one of the samples in the reference block into the first group. Accordingly, the coder classifies the reference samples and samples in the reference block into the plurality of groups.

[0273] In some embodiments, the coder determines (e.g., derives) a plurality of filters. For example, the coder determines a first filter based on sample pairs of reference samples in the first group (group 0) and corresponding current samples, a second filter based on sample pairs of reference samples in the second group (group 1) and corresponding current samples, a third filter based on based on sample pairs of reference samples in the third groupDocket No.: 23-2054PCT (group 2) and corresponding current samples, a fourth filter based on based on sample pairs of reference samples in the fourth group (group 3) and corresponding current samples, and a fifth filter based on based on sample pairs of reference samples in the fifth group (group 4) and corresponding current samples. Note each filter for each group is determined based on reference samples of the reference template and corresponding current samples of the current template. Although this example is described with respect to four classified groups and four respective filters (e.g., multi-parametric filters), the same mechanisms may be performed for samples classified into at least two groups.

[0274] In some embodiments, the coder determines a prediction block by applying the first filter to samples in the reference block in the first group (group 0), by applying the second filter to samples in the reference block in the second group (group 1), by applying the third filter to samples in the reference block in the third group (group 2), by applying the fourth filter to samples in the reference block in the fourth group (group 3), and by applying the fifth filter to samples in the reference block in the fifth group (group 4). Although this example is described with respect to four classified groups and four respective filters (e.g., multi-parametric filters), the same mechanisms may be performed for samples classified into at least two groups.

[0275] In some embodiments, an encoder determines (e.g., codes, generates) a prediction error (e.g., residual) based on the difference between a block being encoded and the prediction block. The encoder may signal the prediction error into a bitstream to encoder the current block. In some embodiments, a decoder determines (e.g., codes, reconstructs) the current block based on the prediction block and the residual obtained (e.g., received) from the bitstream (e.g., signaled by the encoder).

[0276] FIGS.28B-C show example Laplacian filters, which are examples of edge detection filters used in activity classification, as described in FIG.28A. Each filter is applied sample-by-sample to each reference sample (e.g., from a reference block and / or a reference template of the reference block). The center of each filter corresponds to the sample on which the filter is applied and the value of the sample along with values of surrounding neighboring samples (e.g., up to 8 adjacent samples) of the center sample are used to generate a filtered value. FIG.28B shows an example vertical Laplacian filter. As discussed, in some embodiments, the activity classifier 2800 applies the vertical Laplacian filter through convolution with the image. FIG.28C shows an example horizontal Laplacian filter. As discussed, in some embodiments, the activity classifier 2800 applies the horizontal Laplacian filter through convolution with the image.

[0277] FIG.29A is a schematic view of an activity classifier 2900 of a coder (e.g., encoder 200, decoder 300), according to some embodiments. As illustrated, in some embodiments, activity classifier 2900 is configured to classify at least some samples in a reference picture (e.g., reference picture 1706). As shown, in some embodiments, activity classifier 2900 classifies reference samples (e.g., luma components of pixels) neighboring a reference block (e.g., reference samples in template 1716 of the reference block 1708, reference samples in template 1814 of the reference block 1810) and / or reference block samples (e.g., luma components of pixels) in the reference block (e.g., samples in the reference block 1708, samples in the reference block 1810) into a plurality of groups (e.g., first group, second group).Docket No.: 23-2054PCT

[0278] In some examples, similar to activity classifier 2800, activity classifier 2900 may be a type of feature-based classifier in which activity levels of samples in the reference block are determined and used to classify those samples into the plurality of groups. For example, activity classifier 2800 may include a plurality of edge detection filters such as a first plurality of Laplacian filters related to detecting directional-based edges and such as a second plurality of Laplacian filters for detecting vertical and / or horizontal edges.

[0279] For example, as shown, activity classifier 2900 includes a vertical Laplacian filter 2902 and a horizontal Laplacian filter 2904, which may be similar to first Laplacian filter 2802 and second Laplacian filter 2804, respectively. As discussed, vertical Laplacian filter 2902 is configured to emphasize and detect vertical edges in an image (image including the reference block samples and reference samples in this example). As discussed, horizontal Laplacian filter 2904 is configured to emphasize and detect horizontal edges in the image (image including the reference block samples and reference samples in this example).

[0280] As shown, the vertical Laplacian filter 2902 receives the image (image including reference samples and / or samples from the reference block in this example). In this example, the activity classifier 2900 applies the vertical Laplacian filter 2902 through convolution with the image. As a result, the vertical Laplacian filter 2902 determines (e.g., generates) a fourth filtered image including fourth filtered samples.

[0281] As shown, the horizonal Laplacian filter 2904 receives the image (image including reference samples and / or samples from the reference block in this example). In this example, the activity classifier 2900 applies the horizontal Laplacian filter 2904 through convolution with the image. As a result, the horizontal Laplacian filter 2904 determines (e.g., generates) a fifth filtered image including fifth filtered samples.

[0282] As shown, in some embodiments, activity classifier 2900 includes a first combiner 2906 (e.g., first adder) that is configured to combine the fourth filtered image and the fifth filtered image. As a result, the first combiner 2906 determines (e.g., generates) a first combined image including first combined samples. In this example, the first combined sample is also referred to as a first sum of a fourth filtered sample from the vertical Laplacian filter 2902 and a fifth filtered sample from the horizontal Laplacian filter 2904 corresponding to the fourth filtered sample.

[0283] In some examples, the plurality of edge detection filters such as vertical Laplacian filter 2902 and horizontal Laplacian filter 2904 may be applied sample-by-sample to each sample (x,y) from the reference block and / or the reference template to generate a value representing the combination (shown as first sums in FIG.29A) of applying the plurality of edge detection filters to each sample. Thus, first combiner 2906 outputs, sample by sample, the value representing the combination of multiple Laplacian filters applied to each sample.

[0284] As shown, in some embodiments, the activity classifier 2900 includes an activity index indicator 2908 that is configured to indicate an activity index (v) for each first sum (combined sample of the fourth filtered sample and fifth filtered sample in this example) sample-by-sample of each sample (x,y). In some embodiments, the activity index indicator 2908 determines the activity index (v) for each first sum representing the sum of outputs of the plurality of edge detection filters (e.g., vertical Laplacian filter 2902 and horizontal Laplacian filter 2904) applied to each sample (x,y) as follows:Docket No.: 23-2054PCT vi= min (15, (1407 × 3 × first sum) >> (9 + bitdepth))

[0285] In some embodiments, the “bitdepth” in the code is 8. In some embodiments, the “bitdepth” in the code is 10. In this example, the bitdepth is 10.

[0286] As shown, the activity index indictor 2908 is configured to determine an activity for each first sum based on the activity indexes (v) of the first sums (of the combined values) and a lookup table 2930.

[0287] As shown, in some embodiments, the activity classifier 2900 includes a second plurality of edge detection filters (e.g., a second plurality of Laplacian filters) that includes a first Laplacian filter 2922, a second Laplacian filter 2924, …, and an N-th Laplacian filter 2926. In this example, the first Laplacian filter 2922 is a vertical Laplacian filter, the second Laplacian filter 2924 is a horizontal Laplacian filter, and the N-th Laplacian filter 2926 (also referred to as third Laplacian filter in this disclosure) is a diagonal Laplacian filter. In some embodiments, the N-th Laplacian filter 2926 is a diagonal Laplacian filter (from top-left to bottom-right). In some embodiments, the N-th Laplacian filter 2926 is a diagonal Laplacian filter (from top-right to bottom-left). In some embodiments, the activity classifier 2900 includes both the diagonal Laplacian filter (from top-right to bottom-left) and diagonal Laplacian filter (from top-left to bottom- right). For example, the second plurality of Laplacian filters may include a plurality of diagonal Laplacian filters and / or horizontal and vertical Laplacian filters. As a result, a second combiner 2928, which will be described in more detail, combines four filtered images.

[0288] Similar to vertical Laplacian filter 2902 and horizontal Laplacian filter 2904, when the first Laplacian filter 2922 is the vertical Laplacian filter, the first Laplacian filter 2922 is configured to emphasize and detect vertical edges in an image (image including the reference block samples and reference samples in this example). And when the second Laplacian filter 2924 is the horizontal Laplacian filter, the second Laplacian filter 2924 is configured to emphasize and detect horizontal edges in the image (image including the reference block samples and reference samples in this example). When the third Laplacian filter 2926 is the diagonal Laplacian filter, the third Laplacian filter 2926 is configured to emphasize edges in a diagonal direction in the image (image including the reference block samples and reference samples in this example).

[0289] As shown, the first Laplacian filter 2922 receives the image (image including reference samples and samples from the reference block in this example). In this example, the activity classifier 2900 applies the first Laplacian filter 2922 (vertical Laplacian filter in this example) through convolution with the image. As a result, the first Laplacian filter 2922 determines (e.g., generates) a first filtered image including first filtered samples.

[0290] As shown, the second Laplacian filter 2924 receives the image (image including reference samples and samples from the reference block in this example). In this example, the activity classifier 2900 applies the second Laplacian filter 2924 (horizontal Laplacian filter in this example) through convolution with the image. As a result, the second Laplacian filter 2924 determines (e.g., generates) a second filtered image including second filtered samples.

[0291] As shown, the third Laplacian filter 2926 receives the image (image including reference samples and samples from the reference block in this example). In this example, the activity classifier 2900 applies the thirdDocket No.: 23-2054PCT Laplacian filter 2926 (diagonal Laplacian filter in this example) through convolution with the image. As a result, the third Laplacian filter 2926 determines (e.g., generates) a third filtered image including third filtered samples.

[0292] As shown, in some embodiments, the activity classifier 2900 includes a second combiner 2928 (e.g., second adder) that is configured to combine the filtered images including the first filtered image, second filtered image, and third filtered image) from the plurality Laplacian filters (including the first Laplacian filter 2922, second Laplacian filter 2924, and third Laplacian filter 2926). As a result, the second combiner 2928 determines (e.g., generates) a second combined image including second combined samples. In this example, the second combined sample is also referred to as a second sum of a first filtered sample from the first Laplacian filter 2922, a second filtered sample from the second Laplacian filter 2924 corresponding to the first filtered sample, and a third filter sample from the third Laplacian filter 2926 corresponding to the first filtered sample.

[0293] In some examples, the second plurality of edge detection filters Laplacian filters 2922-2926 may be applied sample-by-sample to each sample (x,y) from the reference block and / or the reference template to generate a value representing the combination (shown as second sums in FIG.29A) of applying the plurality of edge detection filters to each sample. Thus, second combiner 2928 outputs, sample by sample, the value representing the combination of multiple Laplacian filters applied to each sample.

[0294] As shown, in some embodiments, the activity classifier 2900 includes a filter response normalizer 2910. In some embodiments, the filter response normalizer 2910 normalizes the output of second combiner 2928 based on a number of Laplacian filters and an activity level (e.g., activity index) to generate normalized values (e.g., representing sample values of reference block being normalized into a corresponding normalized image) as follows: Normalized value = (second combined sample / N) >> Activity

[0295] ‘N’ indicates the number of the Laplacian filters (e.g., 3 in this example) and Activity is from the activity index indicator 2908. Accordingly, the directionality property of a sample (at a position (x,y)) as represented by the sum of outputs (second sums output from second combiner 2928) of the second plurality of edge detection filters (e.g., Laplacian filters 2922-2926) may be normalized based on dividing by the number of the second plurality of edge detection filters and further divided (e.g., right shifted) by the activity (e.g., activity index).

[0296] As shown, in some embodiments, the activity classifier 2900 includes a classifier 2912 that is configured to classify the normalized values (also referred to as normalized samples in this disclosure) from filter response normalizer 2910 based on one or more thresholds. In this example, classifier 2912 classifies the normalized samples into two groups (e.g., first group (group 0), second group (group 1)) based on a predetermined threshold. In some embodiments, classifier 2912 classifies the normalized samples into three or more groups.

[0297] In some embodiments, the coder classifies the reference samples and samples in the reference block into a plurality of groups (first group (group 0) and second group (group 1) in this example) based on the classification result from the classifier 2912. For example, when the classifier 2912 classifies a first normalized sample at a first position of the normalized image into the first group, the coder determines a first sample at a first position of the image (corresponding to the first position of the normalized image) into the first group. When the first position is associatedDocket No.: 23-2054PCT with the one of the reference samples, the coder classifies the one of the reference samples into the first group. When the first position is associated with the one of the samples in the reference block, the coder classifies the one of the samples in the reference block into the first group. Accordingly, the coder classifies the reference samples and samples in the reference block into the plurality of groups.

[0298] In some embodiments, the coder determines (e.g., derives) a plurality of filters. For example, the coder determines a first filter based on sample pairs of reference samples in the first group (group 0) and corresponding current samples and a second filter based on sample pairs of reference samples in the second group (group 1).

[0299] In some embodiments, the coder determines a prediction block by applying the first filter to samples in the reference block in the first group (group 0), and by applying the second filter to samples in the reference block in the second group (group 1). Note each filter for each group is determined based on reference samples of the reference template and corresponding current samples of the current template. Although this example is described with respect to two classified groups and two respective filters (e.g., multi-parametric filters), the same mechanisms may be performed for samples classified into at least two groups.

[0300] In some embodiments, an encoder determines (e.g., codes, generates) a prediction error (e.g., residual) based on the difference between a block being encoded and the prediction block. The encoder may signal the prediction error into a bitstream to encoder the current block. In some embodiments, a decoder determines (e.g., codes, reconstructs) the current block based on the prediction block and the residual obtained (e.g., received) from the bitstream (e.g., signaled by the encoder).

[0301] FIGS.29B-C show example diagonal Laplacian filters, which are examples of the second plurality of edge detection filters described with respect to FIG.29A. Each filter is applied sample-by-sample to each reference sample (e.g., from a reference block and / or a reference template of the reference block). FIG.29B shows an example diagonal Laplacian filter (from top-right to bottom-left). As discussed, in some embodiments, the activity classifier 2900 applies the diagonal Laplacian filter through convolution with the image. FIG.29C shows an example diagonal Laplacian filter (from top-left to bottom-right). As discussed, in some embodiments, the activity classifier 2800 applies the diagonal Laplacian filter through convolution with the image.

[0302] The following description describe example flowcharts of various methods that may be performed by a coder (e.g., encoder or a decoder). Such a coder may include hardware (circuitry, dedicated logic, one or more processor, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both, which the coder may be included in any computer system or device. For simplicity of explanation, methods described herein are depicted and described as a series of operations. However, operations in accordance with this disclosure may occur in various orders and / or concurrently, and with other operations not presented and described herein. Further, not all illustrated operations may be used to implement the methods in accordance with the disclosed subject matter. In addition, those skilled in the art will understand and appreciate that the methods may alternatively be represented as a series of interrelated states via a state diagram or events. Additionally, the methods disclosed in this specification are capable of being stored on an article of manufacture, such as a non-transitory computer-Docket No.: 23-2054PCT readable medium, to facilitate transporting and transferring such methods to computing devices. The term article of manufacture, as used herein, is intended to encompass a computer program accessible from any computer-readable device or storage media. Although illustrated as discrete blocks, various blocks may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the desired implementation.

[0303] FIG.30 shows a flowchart of an example method 3000 for determining a prediction block, according to some embodiments. The method 3000 may be performed by a coder (e.g., encoder, decoder) that may include hardware (circuitry, dedicated logic, one or more processor, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both, which the coder may be included in any computer system or device.

[0304] At operation 3002, as discussed, the coder (activity classifier of the coder) applies a first Laplacian filter 2802 (vertical Laplacian filter in this example) through convolution with an input image and generates a first filtered image including first filtered samples.

[0305] At operation 3004, as discussed, the coder applies a second Laplacian filter 2802 (horizontal Laplacian filter in this example) through convolution with the input image and generates a second filtered image including second filtered samples.

[0306] At 3006, as discussed, the coder combines the first filtered image and the second filtered image into a combined image including combined samples and determines activity index (v) for each of combined samples (sums) based on the following code. vi = min (15, (1407 × 3 × sum) >> (9 + bitdepth))

[0307] In some embodiments, the “bitdepth” in the code is 8. In some embodiments, the “bitdepth” in the code is 10.

[0308] At operation 3008, as discussed, the coder classifies each of sums based on activity index and lookup table 2812.

[0309] At operation 3010, as discussed, the coder classifies reference samples and samples in the reference block based on the classification result of classifying the sums and determines a plurality of filters.

[0310] At operation 3012, the coder determines a prediction block by applying the plurality of filters to the reference block.

[0311] At operation 3014, the coder codes a current block based on the prediction block. In some embodiments, the coder determines (e.g., codes, generates) a prediction error (e.g., residual) based on the difference between a block being encoded and the prediction block. In some embodiments, the coder determines (e.g., codes, generates) the current block based on the prediction block (and the residual received from another coder (e.g., encoder).

[0312] FIG.31 shows a flowchart of an example method 3100 for determining a prediction block, according to some embodiments. The method 3100 may be performed by a coder (e.g., encoder, decoder) that may include hardware (circuitry, dedicated logic, one or more processor, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both, which the coder may be included in any computer system or device.Docket No.: 23-2054PCT

[0313] At operation 3102, as discussed, the coder (activity classifier of the coder) applies a vertical Laplacian filter 2902 through convolution with an input image and generates a first filtered image including first filtered samples.

[0314] At operation 3104, as discussed, the coder applies a horizontal Laplacian filter 2902 through convolution with the input image and generates a second filtered image including second filtered samples.

[0315] At operation 3106, as discussed, the coder combines the first filtered image and the second filtered image into a first combined image including first combined samples and determines activity index (v) for each of first combined samples (first sums) based on the following code. vi = min (15, (1407 × 3 × first sum) >> (9 + bitdepth))

[0316] In some embodiments, the “bitdepth” in the code is 8. In some embodiments, the “bitdepth” in the code is 10.

[0317] In some embodiments, the coder determines activity for each first sum based on the activity indexes (v) and a lookup table 2930.

[0318] At operation 3108, as discussed, the coder applies a first Laplacian filter 2922 (vertical Laplacian filter in this example) through convolution with the input image and generates a third filtered image including third filtered samples.

[0319] At operation 3110, as discussed, the coder applies a second Laplacian filter 2924 (horizontal Laplacian filter in this example) through convolution with the input image and generates a fourth filtered image including fourth filtered samples.

[0320] At operation 3112, as discussed, the coder applies a third Laplacian filter 2926 (diagonal Laplacian filter) through convolution with the input image and generates a fifth filtered image including fifth filtered samples.

[0321] At operation 3114, as discussed, the coder combines the third filter image, fourth filter image, and fifth filtered image and generates a second combined image including second combined samples. In some embodiments, the coder normalizes the second combined image based on the following code. As a result, coder determines (e.g., generates) a normalized image including normalized values. Normalized value = (second combined sample / N) >> Activity

[0322] ‘N’ in the code indicates the number of the Laplacian filters (3 in this example) and Activity is from the activity index indicator 2908.

[0323] At operation 3116, as discussed, the coder classifies the normalized values into two groups (e.g., first group (group 0), second group (group 1)) based on a predetermined threshold.

[0324] At operation 3118, the coder classifies the reference samples and sample in the reference block based on the classification result of classifying the normalized values and determines a plurality of filters.

[0325] At operation 3120, the coder determines a prediction block by applying the plurality of filters to the reference block.

[0326] At operation 3122, the coder codes a current block based on the prediction block. In some embodiments, the coder determines (e.g., codes, generates) a prediction error (e.g., residual) based on the difference between a blockDocket No.: 23-2054PCT being encoded and the prediction block. In some embodiments, the coder determines (e.g., codes, generates) the current block based on the prediction block (and the residual received from another coder (e.g., encoder).

[0327] FIG.32 is a schematic view of an activity classifier 3200 of a coder (e.g., encoder 200, decoder 300), according to some embodiments. As illustrated, in some embodiments, activity classifier 3200 is configured to classify at least some samples in a reference picture (e.g., reference picture 1706). As shown, in some embodiments, activity classifier 3200 classifies reference samples (e.g., luma components of pixels) neighboring a reference block (e.g., reference samples in template 1716 of the reference block 1708, reference samples in template 1814 of the reference block 1810) and / or reference block samples (e.g., luma components of pixels) in the reference block (e.g., samples in the reference block 1708, samples in the reference block 1810) into a plurality of groups (e.g., first group, second group). Similar to FIG.28A, activity classifier 3200 may be applied sample-by-sample to each sample (x,y) from the reference block and / or the reference template to generate a value representing activity index indicator 3204 corresponding to activity index indicator 2808 of FIG.28A. In some examples, the activity levels indicated by the activity indices determined for samples of the reference block and / or reference template may be classified by a classifier 3206 into one of a plurality of groups (e.g., activity class) similar to classifier 2810. For example, similar to how classifier 2810 may retrieve values from a lookup table 2812, classifier 3206 may obtain a similar lookup table 3208 that maps activity indices to groups (activity class) to classify each sample (x,y) according to activity index indicator 3204 determined for that sample.

[0328] In some examples, different from FIG.28A in which a plurality of edge detection filters are used to determine an activity level represented by the activity index, activity classifier 3200 includes a statistics component 3202 that computes a statistics measure from the plurality of samples in the reference block and / or reference template. For example, the statistics measure may include a standard deviation, a variance, or a combination thereof. Accordingly, activity index indicator 3204 may determine an activity index for a sample (x,y) based on whether the sample value is within a certain range of values based on the statistics measure. For example, the activity index may be represent a multiple of a variance or a standard deviation (which is the square root of the variance). For example, an index of 0 may indicate the sample value being within a range of values that is based on one times the standard deviation or the variance. For example, an index of 1 may indicate the sample value being in a range of values that is based on two times the standard deviation or the variance.

[0329] In some embodiments, the activity index indicator 3204 may generate an activity index for each sample (x,y) that is used to normalize outputs of a plurality of edge detection filters applied to sample (x,y). For example, the Laplacian filters 2902-2904 in FIG.29A used by activity index indicator 2908 may be replaced by statistics component 3202.

[0330] FIG.33 shows a flowchart of an example method 3300 for classifying reference samples associated with a reference block based on detecting, at least from samples of the reference block, one or more feature related to activity (e.g., activity level or activity index indicating change in intensities), according to some embodiments. The method 3300 may be performed by a coder (e.g., encoder, decoder).Docket No.: 23-2054PCT

[0331] At operation 3304, the coder determines, for each sample of the reference block and of the plurality of reference samples neighboring the reference block, a value representing first filtered values resulting from applying a first plurality of edge detection filters to each sample. For example, the first plurality of edge detection filters may be Laplacian filters, as described above with respect to FIGS.28-19. The value may be used to determine an activity (e.g., activity index or activity level), for example, as output by activity index indicator 2808 of FIG.28A, activity index indicator 2908 of FIG.29A, or second combiner 2928 of FIG.29A.

[0332] In some examples, the first plurality of Laplacian filters includes at least one diagonal Laplacian filter. In some examples, the first plurality of Laplacian filters includes a vertical Laplacian filter, a horizontal Laplacian filter, and the at least one diagonal Laplacian filter. For example, the at last one diagonal Laplacian filter may include at least one top-left to bottom right diagonal Laplacian filter or at least one top-right to bottom-left diagonal Laplacian filter.

[0333] In some examples, the value may be a normalized value determined based on determining an activity value based on combining second filtered values resulting from applying a second plurality of Laplacian filters to each sample. Then, the normalized value may be determined based on the first filtered values and the activity value, as explained above with respect to FIG.29B. In some examples, the second plurality of Laplacian filters include a vertical Laplacian filter and a horizontal Laplacian filter. In some examples, the second plurality of Laplacian filters exclude diagonal Laplacian filters.

[0334] In some examples, determining the activity value may include determining an activity index based on the combining second filtered value, and determining the activity value based on the activity index and a lookup table.

[0335] At operation, 3306, the coder classifies each sample in the reference block and in the plurality of reference samples based on at least one threshold and the value determined for each sample. For example, the classification may be performed as described above with respect to classifier 2810 of FIG.28A or classifier 2912 of FIG.29A.

[0336] FIG.34 shows a flowchart of an example method 3400 for classifying samples of a reference block based on detecting, at least from samples of the reference block, one or more feature related to directionality of the samples, according to some embodiments. The method 3400 may be performed by a coder (e.g., encoder, decoder).

[0337] At operation 3402, the coder determines values representing directionalities of samples in a reference block and / or reference samples of a reference template of the reference block.

[0338] In some embodiments, the coder may apply a plurality of edge detection filters to determine values representing the determined / detected directionalities of the samples. For example, the edge detection filters may be finite-impulse response (FIR) filters. In some examples, directionality of samples within the reference block may be detected / estimated for a plurality of direction angles (e.g., α =[−75°, −60°, −45°, −30°, −15°, 0°, 15°, 30°, 45°, 60°, 75°, 90°]). For each sample, reference directionalityvalues D78%(α) are determined for each direction angle of the set of angles. In some examples, to determine the reference directionality values D78%(α), the plurality of edge detection filters may include one edge detection filter corresponding to each respective direction angle of the plurality of direction angles. The output of an edge detectionDocket No.: 23-2054PCT filter (of the plurality of edge detection filters) that is the highest indicates an input signa, including the sample, being associated with or containing a feature (e.g., an edge and / or texture) corresponding to the directionality defined for or represented by that edge detection filter.

[0339] In some examples, the plurality of edge detection filters may include a plurality of Gabor filters that each corresponds to an edge at a specific direction in a localized region relative to (e.g., around) a point or region of analysis (e.g., the sample on which the plurality of edge detection filter is applied). In these examples, based on applying the plurality of Gabor filters to a sample, the Gabor filter with the highest output (or response) for that sample may indicate that sample as being associated with the directionality (e.g., direction and localized region) represented by or captured by that Gabor filter.

[0340] In some embodiments, the coder may apply other techniques to determine values representing the determined / detected directionalities of the samples, as will be further explained below.

[0341] In some examples, operation 3402 may include operation 3403, at which the decoder determines one or more thresholds based on the values representing the directionalities.

[0342] For example, values output from a plurality of Gabor filters applied to the samples of the reference block may be used to determine a threshold for each Gabor filter of the plurality of Gabor filters, as will be further explained below.

[0343] At operation 3404, the coder classifies first samples of a current template based on first values, of the values, representing directionalities of the first samples.

[0344] In some examples, operation 3404 may include operation 3405, at which the coder uses the one or more thresholds and the first values to classify the first samples into a plurality of group.

[0345] At operation 3406, the coder classifies second samples of a reference template based on second values, of the values, representing directionalities of the second samples.

[0346] In some examples, operation 3406 may include operation 3407, at which the coder uses the one or more thresholds and the second values to classify the second samples into the plurality of group.

[0347] FIG.35 is a diagram showing an example of using a plurality of thresholds 3506 (T0, T1, …, TM-1) corresponding to a plurality of edge detection filters 3508 to classify samples of a template 3504 of a block 3502, according to some embodiments. In some examples, FIG.35 shows an example of operation 3405 of FIG.34, in which case template 3504 may be a current template and block 3502 may be a current block. In some examples, FIG. 35 shows an example of operation 3407 of FIG.34, in which case template 3504 may be a reference template and block 3502 may be a reference block determined for the current block.

[0348] In some examples, the plurality of edge detection filters 3508 may be applied to samples of template 3504 to generate a plurality of reference directionality values D78%(α)for each sample, as explained with respect to FIG.34. As shown, each threshold of the plurality of thresholds may be compared with an output of a respective edge detection filter of the plurality of edge detection filters 3508. Then, for each sample, a value (e.g., an indication) of theDocket No.: 23-2054PCT directionality of the sample may be determined based on which of the outputs of plurality of edge detection filters 3508 is greater than (or equal to) a respective threshold of the plurality of thresholds 3506.

[0349] FIG.36A shows an example of determining one or more thresholds Tref(at block 3610A) using a plurality of directional filters 3608A (e.g., edge detection filters) to determine directionalities of samples of reference block 3602, according to some embodiments. FIG.36B shows an example of determining one or more thresholds Trec (at block 3610B related to reconstructed samples) using a plurality of directional filters 3608B (e.g., edge detection filters) to determine directionalities of samples of current template 3606 of current block 3604, according to some embodiments. In some examples, directional filters 3608A may be the same as the plurality of directional filters 3608B. In some examples, operation 3403 of FIG.34 may include the process described with respect to FIG.36A and / or FIG.36B to determine one or more thresholds.

[0350] In some examples, outputs of directional filters 3608A are accumulated (e.g., shown as summation blocks) across samples of reference block 3602 to determine the one or more thresholds Tref. As described above with respect to FIG.35, the one or more threshold values may be used to classify samples of a reference template of the reference block. In some examples, as described above with respect to FIG.35, the one or more threshold values may be used to classify samples of a current template of the current block.

[0351] In some examples, the one or more threshold values may be determined based on determining N maximum values of the accumulated outputs and selecting M directional filters (of directional filters 3608A) corresponding to the M maximal values of the accumulated outputs.

[0352] In some examples, directional filters 3608A may include a plurality of Gabor filters of different frequencies indicated by a Gabor parameter (e.g., σ “Sigma” parameter). The Gabor parameters of the plurality of Gabor filters may be set or configured based on one or more of the following: a template size, a size of a predicted block (e.g., current block 3604), and / or whether component of the predicted color plane is of luminance or chrominance type. For example, based on the template size, an example Gabor parameter may be set equal to a number of lines in the reference template minus 2. In another example, the Gabor parameter may be set as a number of lines in the reference template. For example, based on the size of the predicted block, the Gabor parameter may be set to 3 for smaller blocks (e.g., 64 samples or less) and set to the number of lines in the template for larger blocks (e.g., greater than 64 samples). For example, based on the component of the predicted color plane, the Gabor parameter value may be set to larger values for the chrominance color plane.

[0353] In some examples, a directionality threshold value for a corresponding filter of directional filters 3608A may be determined based on dividing an accumulated output value by the number of displacements of the corresponding filter.

[0354] In some examples, a directionality threshold value for the corresponding filter may be determined based on the maximum output value of the filter.

[0355] Directionality of samples of a reference template of reference block 3602 may be determined by applying directional filters 3608A to the samples and comparing outputs of directional filters 3608A to corresponding thresholdsDocket No.: 23-2054PCT (as determined at block 3610A). In some examples, a sample is classified to a group (e.g., class) of a plurality of groups when the output of a filter, of directional filters 3608A, applied in position of this sample within reference block 3602 or the reference template results in a value greater than the threshold associated with that filter.

[0356] In some examples, directionality of samples of current template 3606 may be similarly determined by applying directional filters 3608A to those samples and comparing outputs of directional filters 3608A to the corresponding thresholds. For example, a reference sample may be classified in a group corresponding to one directional filter based on that sample and the corresponding sample (e.g., colocated) in current template 3606 each being greater (or equal) to the threshold associated with that directional filter.

[0357] In some examples, classification mismatch may be determined for a sample at sample position (x,y) based on determining: - the maximum value Vref_max of the output of directional filters 3608A (F0…FN-1) when applied to the reference template at position (x,y); and - the maximum value Vrec_maxof the output of direction filters 3608B (which may be the same as directional filters 3608A) when applied to current template 3606 at corresponding (colocated) position (x’,y’). Two samples may correspond to each other or colocated if they are at the same relative positions in their respective templates. In other words, (x’-PUx, y’-PUy) is equal to (x-REFx, y-REFy), where PU is a top-left position of current block 3604 and REF is a position of a reference block 3602 within a reference picture. In some examples, classification mismatch may be determined for the sample based on one of the following conditions:Samples that have classification mismatches may be skipped when determining parameters of a filter to be applied to samples of a reference block classified in the same group.

[0358] FIG.37 shows a flowchart of an example method 3700 for determining values representing directionalities of samples of a reference block based on generating a histogram of gradients (HoG), according to some embodiments. For example, a value representing a directionality may be a gradient alpha (e.g., direction or angle) of a bin in the HoG. The method 3400 may be performed by a coder (e.g., encoder, decoder).

[0359] In some embodiments, method 3700 may be one example of determining the values representing directionalities as described above with respect to operation 3402 of FIG.34.

[0360] At operation 3702, each sample (x, y) from a set of samples (Pref) is obtained on which gradient analysis is performed to generate the HoG. In some examples, the set of samples include samples of the reference block. In some examples, the set of samples include samples of a template reference of the reference block. In some examples, the set of samples include both samples of the reference block and the template reference.Docket No.: 23-2054PCT

[0361] At operation 3704, a horizontal difference or gradient at the position of the sample may be determined based on applying a horizontal spatial filter as shown in FIG.38A. At operation 3706, a vertical difference or gradient at the position of the sample may be determined based on applying a vertical spatial filter as shown in FIG.38B. For example, the horizontal and vertical spatial filters of FIGS.38A-B may be Sobel filters. As shown in FIGS.38A-B, for each sample at the center (C) position, a spatial filter is applied to the sample and neighboring samples of that sample indicated by cardinal directions and intercardinal (or ordinal) directions. Each spatial filter includes a set of coefficients corresponding to specific neighboring samples (indicated by the cardinal and intercardinal directions) of the sample.

[0362] At operation 3708, a gradient (e.g., tangent value of an angle of gradient) is determined based on a ratio of the horizontal difference (dx) to the vertical difference (dy) (e.g., alpha= dx / dy). The gradient α may correspond to a bin at a specific index of the HoG.

[0363] At operation 3710, a magnitude value of the gradient (e.g., absolute value) of the gradient may be determined. In some examples, the magnitude value may be determined as a sum of the absolute values of the horizontal difference and the vertical difference. In some examples, the magnitude may be determined as a sum of squared magnitudes, i.e., grad_abs = dx2+ dy2.

[0364] At operation 3712, the HoG is updated based on the calculated gradient at operation 3708 and the calculated magnitude at operation 3710. In some examples, a magnitude at an index of bin, of the HoG, corresponding to the calculated gradient (e.g., tangent value of angle of gradient) may be updated by the calculated magnitude, e.g., HoG[alph] += grad_abs. In some examples, an array of counters for the HoG may be additional incremented by one at the same index to indicate a number of instances that the magnitude at that bin in the HoG has been updated, e.g., HoG_cnt[alpha] += 1.

[0365] In some examples, the maximum value of HoG may be obtained to determine an estimation of the directionality of samples within a set of samples (e.g., in a reference block, a reference template, and / or the reference block and the reference template).

[0366] In some examples, at operation 3714 shown in dotted lines, the magnitudes in the HoG may be normalized. For example, each non-zero magnitude stored in the HoG may be divided by the value of the array of counters corresponding to the bin at which the non-zero magnitude is stored in the HoG. That is, a non-zero magnitude at a first index in the HoG may be divided by a counter value at the same first index in the array of counters. The first index in each of the HoG and the array of counters represent information accumulated for the same direction / angle / gradient. In some examples, the maximum value of a normalized HoG may be obtained to determine an estimation of the directionally of samples within the set of samples.

[0367] In some embodiments, the HoG (or normalized HoG) determined by method 3700 may be used to determine a threshold value, such as the one or more threshold values determined at operation 3403 of FIG.34. In some examples, the threshold value may be obtained from the HoG based on one of the following: a maximum value withinDocket No.: 23-2054PCT a normalized HoG, a median value within a normalized HoG, or a maximum value of a HoG divided by the number of samples within the number of samples from which the HoG was estimated.

[0368] In these embodiments, this threshold value may be used to classify each sample into a plurality of groups / classes based on values of that sample and neighboring samples of that sample. For example, this threshold value may be used to classify first samples of a current template of the current block, as described with respect to operation 3405 of FIG.34, and / or classify second samples of a reference template of the reference block, as described with respect to operation 3407 of FIG.34.

[0369] FIG.39 shows an example of a plurality of spatial filters used to determine a value representing a directionality of a sample on which the plurality of spatial filters is applied, according to some embodiments. For example, the plurality of spatial filter may be a plurality of orientation / directional filters such as a vertical filter, a first diagonal filter (e.g., top right to bottom left), a horizontal filter, and a second diagonal filter (e.g., top left to bottom right). In some examples, the plurality of spatial filters may be applied to samples of a reference template of a reference block and / or of a current template of a current block to classify the samples into a plurality of groups. As explained above, classified samples of the reference template and / or the current template may be used to determine a filter (e.g., a multi-parametric filter) and derive parameter(s) of the filter for each group of classified samples. Then, the plurality of spatial filters may be applied to samples of the reference block to classify those samples into the plurality of groups with each determined filter applied to each respective group to determine the prediction block.

[0370] In some examples, the plurality of spatial filters may be applied to a sample (at the center C position) and neighboring samples (indicated by cardinal and ordinal directions) with respective weights (e.g., ranging from -1 to 2) to obtain a plurality of filter values (e.g., “delta” values) used to classify that sample. In some examples, the maximum value of the plurality of filter values is determined as the maximum absolute value from the obtained plurality of filter values.

[0371] In some embodiments, the plurality of groups (also referred to as types or classes) may include a smooth group, a notch group, and / or a ridge group. For example, a sample may be classified as being in the smooth group based on the absolute value of the maximum value is less than a threshold value. For example, the sample may be classified to be of the notch group based on the absolute value of the maximum value being negative and smaller than the negated value of the threshold value. For example, the sample may be classified to be of the ridge group based on the absolute value of the maximum value being positive and greater than the threshold value. In some examples, each sample may be assigned a value indicating the group / class to which it is classified (e.g., the value being 2 for smooth, 0 for notch, and 4 for ridge).

[0372] In some examples, the threshold value may be determined based on the HoG, as explained above with respect to FIGS.37-38.

[0373] In some embodiments, a binary mask may be specified for a reference template of the reference block and / or the reference block and used to classify the samples as being in one of two groups: a smooth group or a non-Docket No.: 23-2054PCT smooth group. In these embodiments, if the maximum value (e.g., “delta” value) is less than the threshold value, a sample is classified to be of the smooth group Otherwise, the sample is classified to be of the non-smooth group.

[0374] In some examples, after obtaining the binary mask for the reference block and / or the reference template indicating whether a sample is in the smooth group or the non-smooth group, the binary mask may be adjusted to reduce or eliminate discontinuities. For example, one or more of the following adjustments may be applied: a scaling operation, a smoothing operation, and / or thresholding operation. In an example, all three operations are performed with the scaling operation being performed first, then the smoothing operation, then the threshold operation.

[0375] In the scaling operation, instead of the value of “1”, this value may be scaled by left shifting a number of bits (prec) which is the same as multiplying by a value corresponding to the shift. For example, prec may be set equal to 4. For example, the value of “1” may be scaled by determining as 1<<prec are used, where “prec+1” is the number of bits defined for smoothing operations. As a result of this replacement, the new classifier matrix may contain just 0 and 1<<prec values.

[0376] In the smoothing operation, a spatial smoothing filter (e.g., FIR filter) may be applied to the obtained classifier matrix. For example, the spatial filter may be defined as [111; 181; 111] / 16. It is to be understood, that the first mask scaling operation may be combined with filter applying operation and in this case, a spatial filter is determined to be non-normalized, e.g. [111; 181; 111].

[0377] In the thresholding operation, a threshold may be obtained to filtered classifier matrix. For example, the threshold may be determined based on scaling the scaled value (1<<prec) by a fixed value (i.e., threshold = (1<<prec) * K). The value of K may be constant and be, e.g., 0.2, 0.4, 0.75. Values that are greater than the determined threshold may be assigned to 1 and the values that are smaller than the threshold may be set to 0.

[0378] In some examples, classifier matrix smoothing may be performed several times to achieve a stronger smoothing effect. In some examples, a larger spatial FIR filter may be applied to a classifier matrix.

[0379] In other embodiments, “weak notch”, “strong notch”, “weak ridge” and “strong ridge” groups (also referred to as types or classes) may be defined and used based on two threshold values. For example, to classify a sample, two threshold values are used, T1 and T2, such that T1≥0, T2≥0, T2>T1. Each group may be assigned or be associated with a value. For example, the groups may be denoted with values as follows: “strong notch” group is assigned a value of 0, “weak notch” is assigned a value of 1, “weak ridge” group is assigned a value of 3, and the “strong ridge” group is assigned a value of 4. When the value of the maximum value (“delta”) is negative and it is smaller than the negated value of the threshold T2, a sample is classified to the “strong notch” group. Otherwise, when the value of the maximum value is negative and it is smaller than the negated value of the threshold T1, a sample is classified to the “weak notch” group. When the value of the maximum value is positive and is greater than the T2 threshold then the sample is classified as a “strong ridge” group. Otherwise, when the value of the maximum value is positive and is greater than the T1threshold then the sample is classified as a “weak ridge” group. Correspondingly, in these embodiments, five groups may be used, and are selectively applied to samples of a reference block. Selection isDocket No.: 23-2054PCT performed based on the determined sample classes: “smooth”, “weak notch”, “strong notch”, “weak ridge”, and “strong ridge”.

[0380] In some examples, any of the embodiments described above with respect to FIG.39 may be an example of operation 3404, in which the first samples of the current template are classified.

[0381] In some examples, any of the embodiments described above with respect to FIG.39 may be an example of operation 3406, in which the second samples of the reference template are classified.

[0382] FIG.40 shows an example of selecting values of subsets of spatial neighboring samples of a sample to classify that sample as being in one of a plurality of groups, according to some embodiments.

[0383] In some examples, four subsets of the neighboring samples and their values are selected according to the directional relationship between selected samples in each subset with respect to the sample (at position “C”). For example, each subset may include selecting two neighboring samples from the four cardinal directions or from the four ordinal directions. For example, a first subset may include selecting the North (N) and the South (S) neighbors of the current sample. For example, a second subset may include selecting the Northeast (NE) and the Southwest (SW) neighbors of the current sample. For example, a third subset may include selecting the West (W) and the East (E) neighbors of the current sample. For example, a fourth subset may include selecting the Northwest (Nw) and the Southeast (SE) neighbors of the current sample. The four subsets may correspond to the vertical, a first diagonal (from top right to bottom left), a horizontal, and a second diagonal from top left to bottom right) directions, respectively.

[0384] In some examples, for a selected direction, when the absolute value of the difference of the sample with any of the two spatial neighboring samples is smaller than a threshold, the sample may be classified as a “smooth” group. Otherwise, a comparison of the sample value “C” with its neighbors may be performed. For example, a starting classifier value of 2 may be either incremented or decremented depending on whether a neighboring sample is greater than the sample (at center C) or smaller than the sample. As the result of these operations, a starting classifier value may be modified and falls within a range of [0;4]. A classifier group as defined by the modified classifier value may be determined, e.g., based on the following table:template and / or the samples of the reference block.

[0386] In some examples, the threshold may be a predetermined value.Docket No.: 23-2054PCT

[0387] In some examples, the threshold may be determined based on calculating a HoG, as described above with respect to FIG.37.

[0388] In some examples, a direction, corresponding to one of the four subsets, may be selected based on calculating the maximum absolute value of differences between the current sample “C” and each of the two spatial neighbors for each of the directions corresponding to the for subsets. Then, one of the subsets may be selected that has the maximum absolute value of the differences among all of the four subsets.

[0389] FIG.41 shows a flowchart of an example method 4100 for applying feature-based classification to reference block samples and applying multi-parametric filters to the classified samples of the reference block to predict a current block, according to some embodiments. The method 4100 may be performed by a coder (e.g., encoder, decoder).

[0390] At operation 4102, the coder classifies, based on one or more features detected from samples of a reference block for the current block, each sample of a plurality of reference samples neighboring the reference block. For example, the plurality of reference samples may be a reference template of (e.g., defined relative to) the reference block.

[0391] In some examples, the one or more features may include activity (e.g., activity level) of the samples of the reference block, as explained above with respect to FIGS.28-31 and FIG.33.

[0392] In some examples, the one or more features may include a statistical measure determined from the samples of the reference block, as explained above with respect to FIG.32.

[0393] In some examples, the one or more features may include values representing directionalities of the samples of the reference block, as explained above with respect to FIG.34. For example, the values representing directionalities may be determined based on applying a plurality of edge detection filters as described above with respect to FIGS.36A-B or FIGS.38A-B. For example, the values representing directionalities may be determined by applying one or more spatial filters, as shown in FIGS.38A-B, to determine a HoG, as described above with respect to FIG.37.

[0394] In some examples, the one or more features may include values representing an edge type / group such as smooth vs non-smooth groups. For example, edge groups may include a smooth group, a notch group, and / or a ridge group. Examples of various edge groups are described above with respect to FIG.39-40.

[0395] In some examples, classifying the each sample in the plurality of reference samples neighboring the reference block (e.g., reference samples of the reference template) may include classifying samples in the plurality of reference samples into a plurality of groups with each sample being classified in one group of the plurality of groups.

[0396] In some examples, each sample in the reference block may be similarly classified into the plurality of groups.

[0397] At operation 4104, the coder determines a plurality of filters based on the classified samples of the plurality of reference samples and corresponding samples neighboring the current block. For example, operation 4104 may correspond to operation 3010 of FIG.30 in which the plurality of filters are determined.

[0398] In some examples, the plurality of filters may be determined for a plurality of corresponding groups in which samples are classified. For example, a respective filter for each classified group of samples may be determined. ForDocket No.: 23-2054PCT example, the coder may determine a first filter of the plurality of filters based on first samples of the plurality of reference samples classified into a first group and corresponding samples neighboring the current block. For example, the coder may determine a second filter of the plurality of filters based on second samples of the plurality of reference samples classified into a second group and corresponding samples neighboring the current block.

[0399] In some examples, each group of classified samples may include a pair of samples including a reference sample (of the reference template) and a corresponding sample of the current template that is each classified in the same group. The reference sample may correspond to the sample in the current template based on both samples being in a same relative position within the reference template and the current template, respectively. In these examples, at operation 4102, samples of the current template of the current block may be similarly classified into the plurality of groups.

[0400] At operation 4106, the coder determines a prediction block by applying the plurality of filters to the classified samples of the reference block. For example, operation 4106 may correspond to operation 3012 of FIG.30 in which the prediction block is determined.

[0401] In some examples, based on there being at least two classified groups, determining the prediction block may include determining a first set of predictions by applying the first filter (determined for the first group) to first samples of the reference block classified into the first group and determining a second set of predictions by applying the second filter (determined for the second group) to second samples of the reference block classified into the second group. Combining the first and second set of predictions (e.g., portions of the prediction block) may result in the determined prediction block.

[0402] At operation 4108, the coder codes the current block based on the determined prediction block. For example, operation 4108 may correspond to operation 3014 of FIG.30 in which the current block is coded.

[0403] In some examples, an encoder may code the current block based on determining a difference between samples of the current block and corresponding samples of the prediction block. The encoder may signal a residual (e.g., prediction error) in a bitstream based on the difference.

[0404] In some examples, a decoder may code (e.g., reconstruct) the current block based on combining the prediction block with the residual obtained from the bitstream.

[0405] Embodiments of the present disclosure may be implemented in hardware using analog and / or digital circuits, in software, through the execution of instructions by one or more general purpose or special-purpose processors, or as a combination of hardware and software. Consequently, embodiments of the disclosure may be implemented in the environment of a computer system (e.g., processing logic) or other processing system. An example of such a computer system 4200 is shown in FIG.42. Blocks depicted in the figures above, such as the blocks in FIGS.1, 2, and 3, may execute on one or more computer systems 4200. Furthermore, each of the steps of the flowcharts depicted in this disclosure may be implemented on one or more computer systems 4200.

[0406] Computer system 4200 includes one or more processors, such as processor 4204. Processor 4204 may be, for example, a special purpose processor, general purpose processor, microprocessor, or digital signal processor.Docket No.: 23-2054PCT Processor 4204 may be connected to a communication infrastructure 4202 (for example, a bus or network). Computer system 4200 may also include a main memory 4206, such as random access memory (RAM), and may also include a secondary memory 4208.

[0407] Secondary memory 4208 may include, for example, a hard disk drive 4210 and / or a removable storage drive 4212, representing a magnetic tape drive, an optical disk drive, or the like. Removable storage drive 4212 may read from and / or write to a removable storage unit 4216 in a well-known manner. Removable storage unit 4216 represents a magnetic tape, optical disk, or the like, which is read by and written to by removable storage drive 4212. As will be appreciated by persons skilled in the relevant art(s), removable storage unit 4216 includes a computer usable storage medium having stored therein computer software and / or data.

[0408] In alternative implementations, secondary memory 4208 may include other similar means for allowing computer programs or other instructions to be loaded into computer system 4200. Such means may include, for example, a removable storage unit 4218 and an interface 4214. Examples of such means may include a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an EPROM or PROM) and associated socket, a thumb drive and USB port, and other removable storage units 4218 and interfaces 4214 which allow software and data to be transferred from removable storage unit 4218 to computer system 4200.

[0409] Computer system 4200 may also include a communications interface 4220. Communications interface 4220 allows software and data to be transferred between computer system 4200 and external devices. Examples of communications interface 4220 may include a modem, a network interface (such as an Ethernet card), a communications port, etc. Software and data transferred via communications interface 4220 are in the form of signals which may be electronic, electromagnetic, optical, or other signals capable of being received by communications interface 4220. These signals are provided to communications interface 4220 via a communications path 4222. Communications path 4222 carries signals and may be implemented using wire or cable, fiber optics, a phone line, a cellular phone link, an RF link, and other communications channels.

[0410] As used herein, the terms “computer program medium” and “computer readable medium” are used to refer to tangible storage media, such as removable storage units 4216 and 4218 or a hard disk installed in hard disk drive 4210. These computer program products are means for providing software to computer system 4200. Computer programs (also called computer control logic) may be stored in main memory 4206 and / or secondary memory 4208. Computer programs may also be received via communications interface 4220. Such computer programs, when executed, enable the computer system 4200 to implement the present disclosure as discussed herein. In particular, the computer programs, when executed, enable processor 4204 to implement the processes of the present disclosure, such as any of the methods described herein. Accordingly, such computer programs represent controllers of the computer system 4200.Docket No.: 23-2054PCT

[0411] In another embodiment, features of the disclosure may be implemented in hardware using, for example, hardware components such as application-specific integrated circuits (ASICs) and gate arrays. Implementation of a hardware state machine to perform the functions described herein will also be apparent to persons skilled in the art.

Claims

Docket No.: 23-2054PCT CLAIMS 1. A method comprising: classifying, based on one or more features detected from samples of a reference block for a current block and of a plurality of reference samples neighboring the reference block, each sample of the reference block and of the plurality of reference samples; determining a plurality of filters based on the classified samples, of the plurality of reference samples, and corresponding samples neighboring the current block; determining a prediction block by applying the plurality of filters to the classified samples of the reference block; and coding the current block based on the prediction block.

2. The method of claim 1, wherein the one or more features comprises an activity level, and wherein the classifying each sample comprises: determining, for the each sample, an activity value based on combining first filtered values resulting from applying a first plurality of edge detection filters to the sample, wherein the sample is classified into a group of a plurality of groups based on the activity value.

3. The method of claim 2, wherein the sample is classified into the group indicated by a lookup table for an activity index corresponding to the activity value.

4. The method of any one of claims 2-3, wherein the first plurality of edge detection filters comprise a vertical Laplacian filter and a horizontal Laplacian filter.

5. The method of claim 4, wherein the first plurality of edge detection filters exclude diagonal Laplacian filters.

6. The method of any one of claims 1-5, wherein the one or more features comprises directionality information obtained using a second plurality of edge detection filters.

7. The method of any one of claims 1-2 or 4-6, wherein the classifying each sample further comprises: determining, for the each sample, a normalized value based on a combination of second filtered values resulting from applying a second plurality of edge detection filters to the sample, wherein the each sample in the reference block and in the plurality of reference samples is classified based on at least one threshold and the normalized value determined for each sample.

8. The method of claim 7, wherein the normalized value is determined based on a combination of the second filtered values and the activity value.

9. The method of claim 8, wherein the normalized value is determined based on: dividing a sum of the second filtered values by a quantity of the second plurality of Laplacian filters; and dividing a resulting quotient by the activity index associated with the activity value.

10. The method of any one of claims 7-9, wherein the second plurality of edge detection filters comprises at least one diagonal Laplacian filter.Docket No.: 23-2054PCT 11. The method of claim 10, wherein the second plurality of edge detection filters comprises a vertical Laplacian filter, a horizontal Laplacian filter, and the at least one diagonal Laplacian filter.

12. The method of any one of claims 10-11, wherein the at least one diagonal Laplacian filter comprises a top-left to bottom-right diagonal Laplacian filter, or a top-right to bottom-left diagonal Laplacian filter.

13. The method of claim 6, wherein the second plurality of edge detection filters, applied to each sample, comprise an edge detection filter corresponding to each respective direction angle of a plurality of direction angles, and wherein the sample is classified based on directionality information represented by outputs of the second plurality of edge detection filters applied to the sample.

14. The method of claim 13, wherein the sample is associated with a direction angle corresponding to the edge detection filter with the highest output value of the outputs, and wherein the sample is classified based on the direction angle.

15. The method of any one of claims 13-14, wherein the second plurality of edge detection filters comprise finite- impulse response (FIR) filters.

16. The method of any one of claims 13-14, wherein the second plurality of edge detection filters comprise comprises Gabor filters.

17. The method of any one of claims 13-16, wherein the sample is classified based on the outputs of the second plurality of edge detection filters and thresholds comprising a threshold for each respective edge detection filter of the second plurality of edge detection filters.

18. The method of claim 17, wherein the thresholds are determined based on applying the second plurality of edge detection filters to the samples neighboring the current block.

19. The method of any one of claims 17-18, wherein the thresholds are determined based on applying the second plurality of edge detection filters to the samples of the reference block.

20. The method of claim 1, wherein the one or more features comprises directionality information obtained using a horizontal Sobel filter and a vertical Sobel filter.

21. The method of claim 20, wherein the each sample is classified based on determining a gradient of the sample obtained from applying the horizontal and vertical Sobel filters to the sample.

22. The method of any claim 20, wherein the each sample is classified based on comparing the gradient with a threshold.

23. The method of claim 22, wherein the threshold is determined based on a histogram of gradients obtained counts of gradients of samples comprising the samples of the reference block or the plurality of reference samples neighboring the reference block.

24. The method of any one of claims 1-23, wherein the classifying each sample in the reference block and in the plurality of reference samples comprises: classifying each sample in the reference block into two groups; and classifying each sample in the plurality of reference samples into the two groups.Docket No.: 23-2054PCT 25. The method of any one of claims 1-24, wherein the determining the plurality of filters comprises: determining a first filter of the plurality of filters based on first samples of the plurality of reference samples classified into a first group and corresponding samples neighboring a current block; and determining a second filter of the plurality of filters based on second samples of the plurality of reference samples classified into a second group and corresponding samples neighboring the current block.

26. The method of claim 25, wherein the determining the prediction block by applying the plurality of filters to the classified samples of the reference block comprises: determining a first portion of the prediction block by applying the first filter to first samples of the reference block classified into the first group; and determining a second portion of the prediction block by applying the second filter to second samples of the reference block classified into the second group.

27. The method of any one of claims 1-26, further comprising: receiving, in a bitstream, an indication of illumination compensation being enabled for the reference block, wherein the classifying is based on the indication of illumination compensation being enabled.

28. The method of any one of claims 1-27, further comprising receiving, in the bitstream, a residual block.

29. The method of claim 28, wherein the coding the current block comprises decoding the current block based on combining the prediction block with the residual block.

30. The method of any one of claims 1-26, further comprising: encoding, in a bitstream, an indication of illumination compensation being enabled for the reference block, wherein the indication of illumination compensation being enabled is based on the current block being coded using the prediction block generated from classified samples of the reference block.

31. The method of any one of claims 1-26 or 30, wherein the coding the current block comprises encoding the current block based on the prediction block.

32. The method of any one of claims 1-26 or 30-31, further comprising: determining a residual block based on the current block and the prediction block; and encoding, in the bitstream, the residual block.

33. A non-transitory computer readable medium storing a bitstream, which, when decoded by a decoder, causes the decoder to perform the method according to any one of claims 1-29.

34. A non-transitory computer-readable recording medium storing a bitstream generated by the method for encoding a video according to any one of claims 1-26 or 30-32.

35. A decoder comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the decoder to perform the method of any one of claims 1-29.

36. An encoder comprising:Docket No.: 23-2054PCT one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the encoder to perform the method of any one of claims 1-26 or 30-32.

37. A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors of an apparatus, cause the apparatus to perform the method of any one of claims 1-32.

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