Method, computing system and computer program for division-free probability regularization for arithmetic coding - Patents.com

Abstract

Various embodiments described herein include methods and systems for coding video. In one aspect, the method includes obtaining video data including a first syntax element having a corresponding alphabet of M elements and obtaining respective occurrence probabilities for the M elements. The method further includes entropy coding a first portion of the video data using the respective occurrence probabilities and encountering the first syntax element during the entropy coding. The method also includes updating the occurrence probabilities based on the first syntax element and determining regularized occurrence probabilities by applying a probability regularization to the updated occurrence probabilities according to at least one of the updated probabilities being less than a threshold probability value, the probability regularization not including a division operation.

Description

[Technical field]

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 319,218, filed March 11, 2022, entitled “Division-free Probability Regularization for Arithmetic Coding,” and is a continuation of and claims priority to U.S. Provisional Patent Application No. 18 / 117,221, filed March 3, 2023, entitled “Systems and Methods for Division-Free Probability Regularization for Arithmetic Coding,” all of which are incorporated herein by reference in their entireties.

[0002] The disclosed embodiments relate generally to video coding and include, but are not limited to, systems and methods for probability regularization for arithmetic coding. [Background technology]

[0003] Digital video is supported by a variety of electronic devices, such as digital televisions, laptop or desktop computers, tablet computers, digital cameras, digital recording devices, digital media players, video game consoles, smart phones, video teleconferencing devices, video streaming devices, etc. These electronic devices transmit, receive, or otherwise communicate digital video data across communication networks and store the digital video data in storage devices. Due to the limited bandwidth capacity of communication networks and limited memory resources of storage devices, video coding may be used to compress the video data according to one or more video coding standards before the video data is communicated or stored.

[0004] Several video codec standards have been developed. For example, video coding standards include AOMedia Video 1 (AV1), Versatile Video Coding (VVC), Joint Search Model (JEM), High Efficiency Video Coding (HEVC / H.265), Advanced Video Coding (AVC / H.264), and Moving Picture Experts Group (MPEG) coding. Video coding generally employs prediction techniques (e.g., inter-prediction, intra-prediction, or the like) that exploit the redundancy inherent in video data. Video coding aims to compress video data into a form that uses a lower bitrate while avoiding or minimizing degradation to video quality.

[0005] HEVC, also known as H.265, is a video compression standard designed as part of the MPEG-H project. ITU-T and ISO / IEC published the HEVC / H.265 standard in 2013 (version 1), 2014 (version 2), 2015 (version 3), and 2016 (version 4). Versatile Video Coding (VVC), also known as H.266, is a video compression standard intended as a successor to HEVC. ITU-T and ISO / IEC published the VVC / H.266 standard in 2020 (version 1) and 2022 (version 2). AV1 is an open video coding format designed as a replacement for HEVC. On January 8, 2019, the certified version 1.0.0 with errata for the specification was released. Summary of the Invention

[0006] As mentioned above, encoding (compression) reduces bandwidth and / or storage space requirements. As will be described in more detail below, both lossless and lossy compression may be used. Lossless compression refers to techniques where an exact replica of the original signal can be reconstructed from the compressed original signal. Lossy compression refers to an encoding / decoding process where the original video information is not fully preserved during encoding and is not fully recoverable during decoding. When using lossy compression, the reconstructed signal may not be identical to the original signal, but the distortion between the original signal and the reconstructed signal will be small enough to make the reconstructed signal useful for the intended application. The amount of distortion that is tolerated depends on the application. For example, a user of a particular consumer video streaming application may tolerate higher distortion than a user of a movie or television broadcast application. The compression ratio achievable by a particular coding algorithm can be selected or adjusted to reflect various distortion tolerances, with higher tolerable distortion generally allowing for coding algorithms that result in higher loss and higher compression ratios.

[0007] The video encoder and / or decoder may utilize techniques from several broad categories and steps, including, for example, motion compensation, Fourier transform, quantization, and entropy coding. During entropy encoding, data related to the process may be sent to an entropy encoder. The entropy encoder may output a bitstream (encoded video sequence), which may be transmitted to another device via a transmission channel. During a video decoding process, the bitstream may be sent to an entropy decoder. Based on the bitstream, the entropy decoder may output data related to the process, which may include intra prediction information, residual information, and the like. In some embodiments, the entropy encoding / decoding utilizes an arithmetic coding algorithm based on the probability of occurrence of symbols (or characters) as the basis for the arithmetic coding. In some embodiments, the probability of occurrence of symbols (or characters) is dynamically updated during the encoding / decoding process. For example, if there are only two possible characters ("a" and "b"), and the probability of "a" occurring is denoted as p_a and the probability of "b" occurring is denoted as p_b, then p_a+p_b=1 (or any other constant value). Thus, when "a" is encountered in the encoding / decoding process, p_a can be updated to a larger value, and since their sum can be constant, p_b can be updated to a smaller value. This probability update process may be referred to as a "probability transition process" or a "probability state index update process."

[0008] According to some embodiments, a method of video coding is provided, comprising the steps of: (i) obtaining video data having a plurality of syntax elements, the plurality of syntax elements including a first syntax element having a corresponding alphabet of M elements, (ii) obtaining respective probabilities of occurrence for the M elements of the first syntax element, (iii) entropy coding a first portion of the video data according to the respective probabilities of occurrence, (iv) encountering the first syntax element while entropy coding the first portion of the video data, and (v) updating the probabilities of occurrence for the M elements according to the first syntax element. (vi) determining regularized probabilities of occurrence for the M elements by applying probability regularization to the updated probabilities of occurrence in accordance with at least one of the updated probabilities for the M elements being less than a threshold probability value, the probability regularization not including a division operation; (b) entropy coding a second portion of the video data in accordance with the regularized probabilities of occurrence; and (vii) entropy coding the second portion of the video data in accordance with the updated probabilities of occurrence in accordance with each of the updated probabilities for the M elements being greater than or equal to the threshold probability value.

[0009] According to some embodiments, a computing system, such as a streaming system, a server system, a personal computer system, or other electronic device, is provided. The computing system includes control circuitry and a memory having stored thereon one or more instruction sets. The one or more instruction sets include instructions for performing any of the methods described herein. In some embodiments, the computing system includes an encoder component and / or a decoder component.

[0010] According to some embodiments, a non-transitory computer readable storage medium is provided that stores one or more sets of instructions for execution by a computing system, the one or more sets of instructions including instructions for performing any of the methods described herein.

[0011] Thus, disclosed are methods, as well as apparatus and systems, for coding video, which may complement or replace conventional methods, apparatus and systems for video coding.

[0012] The features and advantages described herein are not necessarily all-inclusive, and some additional features and advantages will become apparent to those skilled in the art, particularly in light of the drawings, specification, and claims provided in this disclosure. It should also be noted that the language used herein has been selected primarily for ease of reading and instructional purposes, and not necessarily to delineate or bound the subject matter described herein. [Brief description of the drawings]

[0013] So that the present disclosure may be understood in more detail, a more particular description will be made by reference to features of various embodiments, some of which are illustrated in the accompanying drawings, which are, however, merely illustrative of the relevant features of the present disclosure and therefore should not be considered as necessarily limiting, and may, for the purposes of illustration, recognize other useful features as those skilled in the art will read and understand this disclosure. [Figure 1] FIG. 1 is a block diagram illustrating an example of a communication system according to some embodiments. [Figure 2A] FIG. 2 is a block diagram illustrating example elements of an encoder component according to some embodiments. [Figure 2B] FIG. 2 is a block diagram illustrating example elements of a decoder component according to some embodiments. [Diagram 3]FIG. 1 is a block diagram illustrating an example of a server system according to some embodiments. [Figure 4] FIG. 13 is a flow diagram illustrating an example of a flow for decoding a binary decision. [Diagram 5] 5A-5B show example approaches to enforcing minimum probabilities according to some embodiments. [Figure 6] 1 is a flow diagram illustrating an example of a method for coding video according to some embodiments.

[0014] According to common practice, the various features illustrated in the drawings are not necessarily drawn to scale and like reference numerals may be used to refer to like features throughout the specification and drawings. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] This disclosure describes a division-free approach to entropy coding / decoding. For example, a minimum probability is determined, and when each syntax element probability is updated, the updated probability is compared to the minimum probability. In this example, if the updated probability is less than the minimum probability, division-free regularization is performed (e.g., using one or more lookup tables and / or shift operations). In this way, each syntax element probability is prevented from approaching zero, which reduces coding inefficiencies, prevents Bjontegaard delta (BD) rate loss, and / or reduces modeling errors. Furthermore, the division-free approach described herein reduces / eliminates the computational cost associated with performing division operations during the regularization process.

[0016] Examples of systems and equipment 1 is a block diagram illustrating a communication system 100 according to some embodiments. Communication system 100 includes a source device 102 and a number of electronic devices 120 (e.g., electronic devices 120-1 through 120-m) communicatively coupled to each other via one or more networks. In some embodiments, communication system 100 is a streaming system for use with video-enabled applications, such as, for example, video conferencing applications, digital TV applications, and media storage and / or distribution applications.

[0017] Source device 102 includes a video source 104 (e.g., a camera component or media storage) and an encoder component 106. In some embodiments, video source 104 is a digital camera (e.g., configured to create an uncompressed video sample stream). Encoder component 106 generates one or more encoded video bitstreams from the video stream. The video stream from video source 104 may be a larger amount of data compared to encoded video bitstream 108 generated by encoder component 106. Because encoded video bitstream 108 is a smaller amount of data (less data) compared to the video stream from the video source, encoded video bitstream 108 requires less bandwidth to transmit and less storage space to store compared to the video stream from video source 104. In some embodiments, source device 102 does not include encoder component 106 (e.g., configured to transmit uncompressed video data to network(s) 110).

[0018] One or more networks 110 represent any number of networks that carry information between source devices 102, server system 112, and / or electronic devices 120, including, for example, wireline and / or wireless communication networks. One or more networks 110 may exchange data over circuit-switched and / or packet-switched channels. Exemplary networks include telecommunications networks, local area networks, wide area networks, and / or the Internet.

[0019] The one or more networks 110 include a server system 112 (e.g., a distributed / cloud computing system). In some embodiments, the server system 112 is or includes a streaming server (e.g., configured to store and / or distribute video content, such as an encoded video stream from a source device 102). The server system 112 includes a coder component 114 (e.g., configured to encode and / or decode video data). In some embodiments, the coder component 114 includes an encoder component and / or a decoder component. In various embodiments, the coder component 114 is instantiated as hardware, software, or a combination thereof. In some embodiments, the coder component 114 is configured to decode the encoded video bitstream 108 and re-encode the video data using a different encoding standard and / or methodology to generate encoded video data 116. In some embodiments, the server system 112 is configured to generate multiple video formats and / or encodings from the encoded video bitstream 108.

[0020] In some embodiments, server system 112 functions as a Media-Aware Network Element (MANE). For example, server system 112 may be configured to prune encoded video bitstream 108 to tailor potentially different bitstreams to one or more of electronic devices 120. In some embodiments, a MANE is provided separate from server system 112.

[0021] Electronic device 120-1 includes a decoder component 122 and a display 124. In some embodiments, decoder component 122 is configured to decode encoded video data 116 to generate an output video stream that can be rendered on a display or other type of rendering device. In some embodiments, one or more of electronic devices 120 does not include a display component (e.g., is communicatively coupled to an external display device and / or includes media storage). In some embodiments, electronic device 120 is a streaming client. In some embodiments, electronic device 120 is configured to access server system 112 to obtain encoded video data 116.

[0022] Source device and / or electronic devices 120 may be referred to as “terminal devices” or “user devices.” In some embodiments, source device 102 and / or one or more of electronic devices 120 are instances of a server system, a personal computer, a portable device (e.g., a smartphone, tablet, or laptop), a wearable device, a videoconferencing device, and / or other types of electronic devices.

[0023] In an example operation of communication system 100, source device 102 transmits encoded video bitstream 108 to server system 112. For example, source device 102 may code a stream of pictures captured by the source device. Server system 112 may receive encoded video bitstream 108 and decode and / or encode encoded video bitstream 108 using coder component 114. For example, server system 112 may apply more optimal encoding to the video data for network transmission and / or storage. Server system 112 may transmit encoded video data 116 (e.g., one or more encoded video bitstreams) to one or more of electronic devices 120. Each electronic device 120 may decode encoded video data 116 to recover video pictures and, optionally, display them.

[0024] In some embodiments, the transmission is a one-way data transmission. The one-way data transmission may be used in media serving applications and the like. In some embodiments, the transmission is a two-way data transmission. The two-way data transmission may be used in video conferencing applications and the like. In some embodiments, the encoded video bitstream 108 and / or the encoded video data 116 are encoded and / or decoded according to any of the video coding / compression standards described herein, such as, for example, HEVC, VVC, and / or AV1.

[0025] 2A is a block diagram illustrating example elements of the encoder component 106 according to some embodiments. The encoder component 106 receives a source video sequence from a video source 104. In some embodiments, the encoder component includes a receiver (e.g., a transceiver) component configured to receive the source video sequence. In some embodiments, the encoder component 106 receives a video sequence from a remote video source (e.g., a video source that is a component of a different device than the encoder component 106). The video source 104 may provide the source video sequence in the form of a digital video sample stream that may be of any suitable bit depth (e.g., 8-bit, 10-bit, or 12-bit), any color space (e.g., BT.601 Y CrCB, or RGB), and any suitable sampling structure (e.g., Y CrCb 4:2:0, or Y CrCb 4:4:4). In some embodiments, the video source 104 is a storage device that stores pre-captured / prepared video. In some embodiments, the video source 104 is a camera that captures local image information as a video sequence. Video data may be provided as a number of individual pictures that convey motion when viewed in sequence. The pictures themselves may be organized as a spatial array of pixels, with each pixel containing one or more samples, depending on the sampling structure, color space, etc. used. Those skilled in the art will readily understand the relationship between pixels and samples. The following discussion focuses on samples.

[0026] The encoder component 106 is configured to encode and / or compress pictures of a source video sequence into an encoded video sequence (643) in real-time or under other time constraints required by an application. Enforcing an appropriate encoding rate is one function of the controller 204. In some embodiments, the controller 204 controls and is recursively coupled to other functional units, as described below. Parameters set by the controller 204 may include rate control related parameters (picture skip, quantizer, and / or lambda values ​​for rate-distortion optimization techniques, picture size, group of pictures (GOP) layout, maximum motion vector search range, etc. One skilled in the art can readily identify other functions of the controller 204 as they may be relevant for the encoder component 106 to be optimized for a particular system design.

[0027] In some embodiments, the encoder component 106 is configured to operate in a coding loop. In a simplified example, the coding loop includes a source coder 202 (e.g., responsible for creating symbols, e.g., a symbol stream, based on an input picture to be coded and reference picture(s)) and a (local) decoder 210. The decoder 210 reconstructs the symbols to create sample data in a similar manner to a (remote) decoder (when the compression between the symbols and the encoded video bitstream is lossless). The reconstructed sample stream (sample data) is input to a reference picture memory 208. Since the decoding of the symbol stream results in bit-accurate results that are independent of the decoder location (local or remote), the content in the reference picture memory 208 is also bit-accurate between the local and remote encoders. Thus, the prediction part of the encoder interprets the same sample values ​​as reference picture samples that the decoder interprets when using prediction during decoding. This principle of reference picture synchrony (and the resulting drift when synchrony cannot be maintained, e.g., due to channel errors) is known to those skilled in the art.

[0028] The operation of the decoder 210 may be the same as that of a remote decoder, such as the decoder component 122, which is described in more detail below in connection with Figure 2B. However, with brief reference to Figure 2B, the entropy decoding portion of the decoder component 122, including the buffer memory 252 and the parser 254, may not be fully implemented in the local decoder 210 because symbols are available and the encoding / decoding of the symbols into an encoded video sequence by the entropy coder 214 and the parser 254 may be lossless.

[0029] At this point, it can be noted that the decoder techniques, except for parsing / entropy decoding, present in the decoder must necessarily be present in the corresponding encoder in substantially the same functional form. For this reason, the disclosure focuses on the decoder operation. The description of the encoder techniques can be omitted, since they are the inverse of the decoder techniques, which are described in detail. Only in certain areas are further details necessary, which are provided below.

[0030] As part of its operation, the source coder 202 may perform motion compensated predictive coding, which is predictive coding of an input frame with reference to one or more previously coded frames from the video sequence designated as reference frames. Thus, the coding engine 212 codes differences between pixel blocks of the input frame and pixel blocks of the reference frame(s) that may be selected as the prediction reference(s) for the input frame. A controller 204 may manage the coding operations of the source coder 202, including, for example, setting parameters and subgroup parameters used to encode the video data.

[0031] The decoder 210 decodes the encoded video data of frames that may be designated as reference frames based on symbols created by the source coder 202. The operation of the coding engine 212 may advantageously be a lossy process. When the encoded video data is decoded in a video decoder (not shown in FIG. 2A), the reconstructed video sequence may be a replica of the source video sequence with some errors. The decoder 210 may replicate the decoding process that may be performed by a remote video decoder on the reference frames, causing the reconstructed reference frames to be stored in the reference picture memory 208. Thus, the encoder component 106 locally stores copies of reconstructed reference frames that have a common content with the reconstructed reference frames that will be obtained by the remote video decoder.

[0032] The predictor 206 may perform a predictive search for the coding engine 212. That is, for a new frame to be coded, the predictor 206 may search the reference picture memory 208 for sample data (as candidate reference pixel blocks) or specific metadata, such as reference picture motion vectors or block shapes, that may serve as suitable predictive references for the new picture. The predictor 206 may operate on a pixel block by pixel block basis to find suitable predictive references. In some cases, as determined by the search results obtained by the predictor 206, the input picture may have predictive references drawn from multiple reference pictures stored in the reference picture memory 208.

[0033] The outputs of all the aforementioned functional units may be subjected to entropy coding in entropy coder 214. Entropy coder 214 converts the symbols produced by the various functional units into a coded video sequence by losslessly compressing the symbols according to techniques known to those skilled in the art (e.g., Huffman coding, variable length coding, and / or arithmetic coding).

[0034] In some embodiments, the output of the entropy coder 214 is coupled to a transmitter. The transmitter may be configured to buffer the encoded video sequence(s) generated by the entropy coder 214 and prepare them for transmission over a communication channel 218. The communication channel 218 may be a hardware / software link to a storage device that stores the encoded video data. The transmitter may be configured to merge the encoded video data from the source coder 202 with other data to be transmitted, such as encoded audio data and / or auxiliary data streams (sources not shown). In some embodiments, the transmitter may transmit additional data along with the encoded video. The source coder 202 may include such data as part of the encoded video sequence. The additional data may include temporal / spatial / SNR enhancement layers, other forms of redundant data, such as redundant pictures and slices, supplemental enhancement information (SEI) messages, visual usability information (VUI) parameter set fragments, and the like.

[0035] The controller 204 may manage the operation of the encoder component 106. In coding, the controller 204 may assign to each coded picture a particular coded picture type, which may affect the coding technique applied to the respective picture. For example, a picture may be assigned as an intra picture (I picture), a predictive picture (P picture), or a bidirectionally predictive picture (B picture). An intra picture may be coded and decoded without using any other frame in the sequence as a source of prediction. Some video codecs allow several different types of intra pictures, including, for example, Independent Decoder Refresh (IDR) pictures. Those skilled in the art are aware of these variants of I pictures, as well as their respective uses and characteristics, and therefore will not be repeated here. A predictive picture may be coded and decoded using intra prediction or inter prediction, using at most one motion vector and reference index to predict the sample values ​​of each block. Bidirectionally predicted pictures can be encoded and decoded using intra- or inter-prediction, using at most two motion vectors and reference indices to predict the sample values ​​of each block. Similarly, multi-predicted pictures can use more than two reference pictures and associated metadata for the reconstruction of a single block.

[0036] A source picture may generally be spatially subdivided into multiple sample blocks (e.g., blocks of 4x4, 8x8, 4x8, or 16x16 samples each) and coded block by block. Blocks may be predictively coded with reference to other (already coded) blocks determined by the coding assignment applied to their respective pictures. For example, blocks of I-pictures may be non-predictively coded, or they may be predictively coded with reference to already coded blocks of the same picture (spatial or intra prediction). Pixel blocks of P-pictures may be coded non-predictively, or via spatial prediction, or via temporal prediction with reference to one previously coded reference picture. Blocks of B-pictures may be coded non-predictively, or via spatial prediction, or via temporal prediction with reference to one or two previously coded reference pictures.

[0037] A video may be captured as multiple source pictures (video pictures) in a time sequence. Intra-picture prediction (often abbreviated as intra-prediction) uses spatial correlation within a given picture, while inter-picture prediction uses correlation (temporal or other) between pictures. In one example, a particular picture being coded / decoded, called a current picture, is divided into multiple blocks. When a block in the current picture is similar to a reference block in a previously coded and still buffered reference picture in the video, the block in the current picture may be coded by a vector called a motion vector. A motion vector points to a reference block in a reference picture, and may have a third dimension that identifies the reference picture if multiple reference pictures are used.

[0038] Encoder component 106 may perform coding operations according to a given video coding technique or standard, such as any described herein. In so doing, encoder component 106 may perform various compression operations, including predictive coding operations that exploit temporal and spatial redundancy in the input video sequence. Thus, the encoded video data may conform to a syntax defined by the video coding technique or standard used.

[0039] 2B is a block diagram illustrating example elements of the decoder component 122 according to some embodiments. The decoder component 122 of FIG. 2B is coupled to the channel 218 and the display 124. In some embodiments, the decoder component 122 includes a transmitter coupled to the loop filter unit 256 and configured to transmit data to the display 124 (e.g., via a wired or wireless connection).

[0040] In some embodiments, the decoder component 122 includes a receiver coupled to the channel 218 and configured to receive data from the channel 218 (e.g., via a wired or wireless connection). The receiver may be configured to receive one or more encoded video sequences to be decoded by the decoder component 122. In some embodiments, the decoding of each encoded video sequence is independent of the other encoded video sequences. Each encoded video sequence may be received from the channel 218, which may be a hardware / software link to a storage device that stores the encoded video data. The receiver may receive the encoded video data along with other data, such as encoded audio data and / or auxiliary data streams. The other data may be forwarded to their respective usage entities (not shown). The receiver may separate the encoded video sequence from the other data. In some embodiments, the receiver receives additional (redundant) data along with the encoded video. The additional data may be included as part of the encoded video sequence(s). The additional data may be used by the decoder component 122 to decode the data and / or to more accurately reconstruct the original video data. The additional data may be in the form of, for example, temporal, spatial or SNR enhancement layers, redundant slices, redundant pictures, forward error correction codes, and so on.

[0041] According to some embodiments, the decoder component 122 includes a buffer memory 252, a parser 254 (sometimes referred to as an entropy decoder), a scaler / inverse transform unit 258, an intra-picture prediction unit 262, a motion compensated prediction unit 260, an aggregator 268, a loop filter unit 256, a reference picture memory 266, and a current picture memory 264. In some embodiments, the decoder component 122 is implemented as an integrated circuit, a series of integrated circuits, and / or other electronic circuitry. In some embodiments, the decoder component 122 is implemented at least partially in software.

[0042] The buffer memory 252 is coupled between the channel 218 and the parser 254 (e.g., to handle network jitter). In some embodiments, the buffer memory 252 is separate from the decoder component 122. In some embodiments, a separate buffer memory is provided between the output of the channel 218 and the decoder component 122. In some embodiments, in addition to the buffer memory 252 internal to the decoder component 122 (e.g., configured to handle playback timing), a separate buffer memory is provided external to the decoder component 122 (e.g., to handle network jitter). When receiving data from a store / forward device of sufficient bandwidth and controllability or from an isosynchronous network, the buffer memory 252 may not be required or can be made small. For use over a best-effort packet network, such as the Internet, the buffer memory 252 may be required and can be relatively large, advantageously of an adaptable size, and implemented at least in part in an operating system or similar element (not shown) external to the decoder component 122.

[0043] Parser 254 is configured to reconstruct symbols 270 from the coded video sequence. The symbols may include, for example, information used to manage the operation of decoder component 122 and / or information to control a rendering device, such as display 124. The control information for the rendering device(s) may be in the form of, for example, a Supplemental Enhancement Information (SEI) message or a Video Usability Information (VUI) parameter set fragment (not shown). Parser 254 parses (entropy decodes) the coded video sequence. The coding of the coded video sequence may be according to a video coding technique or standard and may follow principles well known to those skilled in the art, including variable length coding, Huffman coding, arithmetic coding with or without context dependency, etc. Parser 254 may extract from the coded video sequence a set of subgroup parameters for at least one of the subgroups of pixels in the video decoder based on at least one parameter corresponding to the group. The subgroups may include a group of pictures (GOP), a picture, a tile, a slice, a macroblock, a coding unit (CU), a block, a transform unit (TU), a prediction unit (PU), etc. Parser 254 may also extract information from the coded video sequence information, such as transform coefficients, quantization parameter values, motion vectors, etc.

[0044] The reconstruction of symbols 270 may involve a number of different units, depending on the type of video picture or portion thereof being coded and other factors (e.g., inter-picture and intra-picture, inter-block and intra-block, etc.). Which units are involved and how they are involved may be controlled by subgroup control information parsed from the coded video sequence by parser 254. The flow of such subgroup control information between parser 254 and the following units is not shown for clarity.

[0045] Beyond the functional blocks already described, the decoder component 122 can be conceptually subdivided into a number of functional units, as described below. In a practical implementation operating under commercial constraints, many of these units may closely interact with each other and be at least partially integrated with each other. However, for purposes of describing the disclosed subject matter, we will maintain the conceptual division into the following functional units:

[0046] The scalar / inverse transform unit 258 receives the quantized transform coefficients and control information (e.g., which transform to use, block size, quantization factor, and / or quantization scaling matrix) as symbol(s) 270 from the parser 254. The scalar / inverse transform unit 258 may output blocks containing sample values ​​that may be input to an aggregator 268.

[0047] In some cases, the output samples of the scaler / inverse transform unit 258 relate to intra-coded blocks, i.e., blocks that do not use prediction information from a previously reconstructed picture, but can use prediction information from a previously reconstructed part of the current picture. Such prediction information can be provided by the intra-picture prediction unit 262. The intra-picture prediction unit 262 may generate a block of the same size and shape as the block being reconstructed using surrounding already reconstructed information fetched from the current (partially reconstructed) picture from the current picture memory 264. The aggregator 268 may add, on a sample-by-sample basis, the prediction information generated by the intra-picture prediction unit 262 to the output sample information provided by the scaler / inverse transform unit 258.

[0048] In other cases, the output samples of the scaler / inverse transform unit 258 relate to a block that may be inter-coded and motion-compensated. In such a case, the motion compensated prediction unit 260 may access the reference picture memory 266 to fetch samples used for prediction. After motion compensating the fetched samples according to the symbols 270 related to the block, these samples may be added by the aggregator 268 to the output of the scaler / inverse transform unit 258 (in this case referred to as residual samples or residual signals) to generate output sample information. The addresses in the reference picture memory 266 from which the motion compensated prediction unit 260 fetches the prediction samples may be controlled by a motion vector. The motion vector may be available to the motion compensated prediction unit 260 in the form of the symbols 270, which may have, for example, X, Y, and reference picture components. Motion compensation may also include interpolation of sample values ​​fetched from the reference picture memory 266 when sub-sample accurate motion vectors are used, motion vector prediction mechanisms, and the like.

[0049] The output samples of aggregator 268 may be subjected to various loop filtering techniques in loop filter unit 256. Video compression techniques may include in-loop filter techniques, which are controlled by parameters included in the coded video bitstream and made available to loop filter unit 256 as symbols 270 from parser 254, but may also be responsive to meta-information obtained during decoding of previous portions of the coded pictures or coded video sequences (in decoding order), as well as to previously reconstructed loop filtered sample values.

[0050] The output of the loop filter unit 256 may be a sample stream that can be output to a rendering device, such as the display 124, which may also be stored in the reference picture memory 266 for use in future inter-picture prediction.

[0051] Once a particular coded picture is fully reconstructed, it can be used as a reference picture for future predictions. Once a coded picture is fully reconstructed and identified as a reference picture (e.g., by parser 254), the current reference picture can become part of reference picture memory 266, and a new current picture memory can be reallocated before starting reconstruction of the next coded picture.

[0052] The decoder component 122 may perform decoding operations according to a given video compression technique, which may be documented in a standard, such as any of the standards described herein. The encoded video sequence may conform to the syntax defined by the video compression technique or standard used, in the sense of adhering to the syntax of the video compression technique or standard defined in the video compression technique document or standard, and specifically in the profile documents therein. Also, for compliance with some video compression techniques or standards, the complexity of the encoded video sequence may be within a range defined by the level of the video compression technique or standard. In some cases, the level constrains the maximum picture size, maximum frame rate, maximum reconstruction sample rate (e.g., measured in megasamples per second), maximum reference picture size, etc. The limits set by the level may in some cases be further constrained through a Hypothetical Reference Decoder (HRD) specification and metadata for HRD buffer management signaled within the encoded video sequence.

[0053] 3 is a block diagram illustrating a server system 112 according to some embodiments. The server system 112 includes a control circuit 302, one or more network interfaces 304, a memory 314, a user interface 306, and one or more communication buses 312 for interconnecting these components. In some embodiments, the control circuit 302 includes one or more processors (e.g., a CPU, a GPU, and / or a DPU). In some embodiments, the control circuit includes one or more field programmable gate arrays (FPGAs), hardware accelerators, and / or one or more integrated circuits (e.g., application specific integrated circuits).

[0054] The network interface(s) 304 may be configured to interface with one or more communication networks (e.g., wireless, wired, and / or optical networks). The communication networks may be local, wide area, metropolitan, vehicular and industrial, real-time, delay tolerant, etc. Examples of communication networks include local area networks, such as Ethernet, wireless LANs, cellular networks including GSM, 3G, 4G, 5G, LTE, and the like, TV wired or wireless wide area digital networks including cable TV, satellite TV, and terrestrial broadcast TV, vehicular and industrial including CANbus, etc. Such communications may be unidirectional receive only (e.g., broadcast TV), unidirectional transmit only (e.g., CANbus to a particular CANbus device), or bidirectional (e.g., to another computer system using a local or wide area digital network). Such communications may include communications to one or more cloud computing networks.

[0055] The user interface 306 includes one or more output devices 308 and / or one or more input devices 310. The input device(s) 310 may include one or more of a keyboard, a mouse, a trackpad, a touch screen, a data glove, a joystick, a microphone, a scanner, a camera, or the like. The output device(s) 308 may include one or more of an audio output device (e.g., a speaker), a visual output device (e.g., a display or monitor), or the like.

[0056] Memory 314 may include high-speed random access memory (such as, for example, DRAM, SRAM, DDR RAM, and / or other random access solid-state memory devices) and / or non-volatile memory (such as, for example, one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, and / or other non-volatile solid-state storage devices). Memory 314 optionally includes one or more storage devices located remotely from control circuitry 302. Memory 314, or alternatively a non-volatile solid-state memory device within memory 314, comprises a non-transitory computer-readable storage medium. In some embodiments, memory 314, or the non-transitory computer-readable storage medium of memory 314, stores the following programs, modules, instructions, and data structures, or a subset or superset thereof: · an operating system 316 that contains procedures for handling various basic system services and for performing hardware dependent tasks; · a network communications module 318 used to connect the server system 112 to other computing devices via one or more network interfaces 304 (e.g., via wired and / or wireless connections); A coding module 320 that performs various functions related to encoding and / or decoding data, such as video data. In some embodiments, the coding module 320 is an instance of the coder component 114. The coding module 320 may include, but is not limited to, one or more of the following: A decoding module 322 that performs various functions related to decoding the encoded data, such as those described above with respect to the decoder component 122; and An encoding module 340 that performs various functions related to encoding data, such as those described above with respect to the encoder component 106; and A picture memory 352 that stores pictures and picture data, e.g., for use with coding module 320. In some embodiments, the picture memory 352 includes one or more of the reference picture memory 208, the buffer memory 252, the current picture memory 264, and the reference picture memory 266.

[0057] In some embodiments, the decoding module 322 includes a parsing module 324 (e.g., configured to perform various functions described above with respect to the parser 254), a transform module 326 (e.g., configured to perform various functions described above with respect to the scaler / inverse transform unit 258), a prediction module 328 (e.g., configured to perform various functions described above with respect to the motion compensation prediction unit 260 and / or the intra-picture prediction unit 262), and a filter module 330 (e.g., configured to perform various functions described above with respect to the loop filter unit 256).

[0058] In some embodiments, the encoding module 340 includes a code module 342 (e.g., configured to perform various functions previously described with respect to the source coder 202, the coding engine 212, and / or the entropy coder 214) and a prediction module 344 (e.g., configured to perform various functions previously described with respect to the predictor 206). In some embodiments, the decoding module 322 and / or the encoding module 340 include a subset of the modules shown in FIG. 3. For example, a shared prediction module is used by both the decoding module 322 and the encoding module 340.

[0059] Each of the above-identified modules stored in memory 314 corresponds to an instruction set for performing functions described herein. The above-identified modules (e.g., instruction sets) need not be implemented as separate software programs, procedures, or modules, and thus, in various embodiments, various subsets of these modules may be combined or otherwise rearranged. For example, coding module 320 optionally does not include separate decoding and encoding modules, but instead uses the same set of modules to perform both sets of functions. In some embodiments, memory 314 stores a subset of the above-identified modules and data structures. In some embodiments, memory 314 stores additional modules and data structures not described above, such as, for example, an audio processing module.

[0060] In some embodiments, the server system 112 includes a web or HyperText Transfer Protocol (HTTP) server, a File Transfer Protocol (FTP) server, and web pages and applications implemented using Common Gateway Interface (CGI) scripts, PHP Hypertext Preprocessor (PHP), Active Server Pages (ASP), Hypertext Markup Language (HTML), Extensible Markup Language (XML), Java, JavaScript, Asynchronous JavaScript+XML (AJAX), XHP, Javelin, Wireless Universal Resource Files (WURFL), and the like.

[0061] FIG. 3 illustrates a server system 112 according to some embodiments, but is intended as a functional illustration of various features that may be present in one or more server systems, rather than a structural schematic of the embodiments described herein. In practice, items shown separately may be combined and some items may be separated, as will be recognized by those skilled in the art. For example, some items shown separately in FIG. 3 may be implemented on a single server, and a single item may be implemented by one or more servers. The actual number of servers used to implement the server system 112, and how features are allocated among them, will vary from implementation to implementation, and optionally depend in part on the amount of data traffic the server system handles during peak and average usage periods.

[0062] Entropy Coding As mentioned above, during entropy coding, data related to the process may be sent to an entropy encoder (e.g., entropy coder 214). The entropy encoder may output a bitstream, which may be transmitted to another device via a transmission channel. During a video decoding process, the bitstream may be sent to an entropy decoder. The entropy decoder may be configured to reconstruct, from the coded picture, certain symbols that represent the syntax elements that make up the coded picture. Such symbols may include, for example, prediction information (e.g., intra- or inter-prediction information) that may identify the mode in which the block is coded (e.g., intra-, inter-, bi-prediction, merged, or other submodes), certain samples or metadata used for prediction by an intra- or inter-decoder, residual information, e.g., in the form of quantized transform coefficients, and the like.

[0063] For example, in HEVC, the entropy coder / decoder may use a context-adaptive binary arithmetic coding (CABAC) algorithm. The CABAC engine in HEVC uses a table-based probability transition process between 64 different representative probability states.

[0064] By applying the syntax elements describing the video frame contents to binary arithmetic coding, the coded stream can be obtained as a binary bin stream. During CABAC, the initial interval [0,1) is stretched by an integer multiplier (e.g., 512), and the least probable symbol probability (pLPS) can be presented as an integer divisor by rounding their quotient. Then, the interval division operation by typical arithmetic coding can be performed as an approximate calculation using integer arithmetic with a specified resolution. The updated interval length (rLPS) corresponding to the LPS can be calculated as rLPS=R*pLPS, where R is the current interval length value. To save time and increase efficiency, the above computationally intensive multiplication operation can be replaced by a look-up table (LUT) populated with pre-computed multiplication results, and thus the updated interval length (ivLpsRange) corresponding to the LPS can be obtained by two indexes pStateIdx and qRangeIdx, for example, as ivlLpsRange=rangeTabLps[pStateIdx][qRangeIdx].

[0065] During encoding / decoding, the probability value pLPS may be recursively updated each time a new value of a bin (binVal) to be encoded / decoded is obtained. For example, at the kth step (i.e., during encoding or decoding of the kth bin), a new value of pLPS may be calculated to be a larger value if binVal is the value of the LPS, or a new value of pLPS may be calculated to be a smaller value if binVal is the value of the most probable symbol (MPS).

[0066] In some embodiments, pLPS may be one of 64 possible values ​​indexed by a 6-bit pStateIdx variable. Updating the probability value may be accomplished by updating the index pStateIdx, which may be performed by looking up the value from a pre-computed table to save computational power and / or improve efficiency.

[0067] In some embodiments, the range ivlCurrRange representing the state of the coding engine may be quantized to a set of four values ​​prior to the calculation of a new interval range. State transitions may be performed by approximating the value of ivlCurrRange*pLPS(pStateIdx) using a table containing all 64×4 8-bit pre-calculated values. Decoding decisions may also be performed using a pre-calculated LUT. First, the LUT is used to obtain ivlLpsRange, and then ivlLpsRange is used to update ivlCurrRange and calculate the output binVal.

[0068] As an example, in VVC, the probability can be linearly represented by the probability index pStateIdx. Thus, all calculations can be done using formulas without LUT operations. To improve the accuracy of the probability estimation, a multi-hypothesis probability update model can be used, as shown in FIG. 4. In this example, pStateIdx used for interval subdivision in a binary arithmetic coder is a combination of two probabilities pStateIdx0 and pStateIdx1. These two probabilities are associated with each context model and updated independently with different adaptation rates. The adaptation rates of pStateIdx0 and pStateIdx1 for each context model can be pre-trained based on the statistics of the associated bin. The probability estimate pStateIdx can be the average of the estimates from the two hypotheses.

[0069] 4 is a flow diagram illustrating an example of a flow (DecodeDecision) for decoding a single decision including a renormalization process (RenomD) in an arithmetic decoding engine. In some embodiments, the inputs to DecodeDecision are a context table (ctxTable) and a context index (ctxIdx). A value for the variable ivlLpsRange is derived as shown at 402. Given the current value of ivlCurrRange, the variable qRangeIdx is derived as qRangeIdx=ivlCurrRange>>5. Given qRangeIdx and the pStateIdx0 and pStateIdx1 associated with ctxTable and ctxIdx, valMps and ivlLpsRange are derived as pState=pStateIdx1+16*pStateIdx0, valMps=pState>>14, and ivlLpsRange=(qRangeIdx*((valMps?32767-pState:pState)>>9)>>1)+4. The variable ivlCurrRange is set to ivlCurrRange-ivlLpsRange.

[0070] If ivlOffset is greater than or equal to ivlCurrRange, then the variable binVal is set equal to 1-valMps, ivlOffset is decremented by ivlCurrRange, and ivlCurrRange is set equal to ivlLpsRange; otherwise, the variable binVal is set equal to valMps.

[0071] In the state transition process, to update the probabilities, the inputs to this process are the current pStateIdx0 and pStateIdx1 and the decoded value binVal, and the output of this process is the updated pStateIdx0 and pStateIdx1 of the context variables associated with ctxTable and ctxIdx. At 404, variables shift0 and shift1 are derived from the shiftIdx value associated with ctxTable and ctxIdx as shift0=(shiftIdx>>2)+2, shift1=(shiftIdx&3)+3+shift0, and according to the decoded value binVal, updates of two variables pStateIdx0 and pStateIdx1 associated with ctxTable and ctxIdx are derived as pStateIdx0=pStateIdx0-(pStateIdx0>>shift0)+(1023*binVal>>shift0) and pStateIdx1=pStateIdx1-(pStateIdx1>>shift1)+(16383*binVal>>shift1).

[0072] As an example, VVC CABAC may have a quantization parameter (QP)-dependent initialization process that is invoked at the beginning of each slice. Given an initial value of luma QP for the slice, the initial probability state of the context model, denoted preCtxState, may be derived by m=slopeIdx×5-45, n=(offsetIdx<<3)+7, and preCtxState=Clip3(1,127,((m×(QP-32))>>4)+n).

[0073] In some embodiments, slopeIdx and offsetIdx are limited to 3 bits, and the total initialization value is represented with 6-bit precision. The probability state preCtxState can directly represent the probability in the linear domain. Therefore, preCtxState may only require a suitable shift operation before input to the arithmetic coding engine, and the mapping from the logarithmic domain to the linear domain and the 256-byte table may be predefined and stored / preserved in memory. pStateIdx0 and pStateIdx1 may be obtained by pStateIdx0=preCtxState<<3 and pStateIdx1=preCtxState<<7.

[0074] In some embodiments, the CABAC algorithm may use a binary basis, which is one that includes two possible characters / symbols (e.g., "0" and "1"). In binary-based arithmetic coding algorithms, the two possible characters / symbols may also be referred to as the least probable symbol (LPS) and the most probable symbol (MPS).

[0075] In some embodiments, an entropy encoder or decoder may use an arithmetic algorithm in an M-ary basis, which includes M possible characters / symbols. For example, M may be any integer value between 2 and 16. For example, if M is equal to 5, then the M-ary basis includes 5 possible characters / symbols that can be represented as "0", "1", "2", "3", and "4".

[0076] An M-ary arithmetic coding engine is used to entropy code syntax elements. Each syntax element is associated with an alphabet of M elements. As an input to an encoder or decoder, a coding context may include a sequence of M-ary symbols with a set of M probabilities. Each of the M probabilities may correspond to each of the M-ary symbols and may be represented by a cumulative distribution function (CDF).

[0077] The cumulative distribution function of the M-ary symbols is C=[c0,c1,…,c (M-2) ,c (M-1) The cumulative distribution function of an M-ary symbol may be represented by an array of M 15-bit integers, where c (M-1) =2 15 and c n / 32768 is the probability that the symbol is less than or equal to n, where n is an integer from 0 to M-1.

[0078] In some embodiments, the M probabilities (e.g., an array of cumulative distribution functions) are updated after coding / parsing each syntax element. In some embodiments, the M probabilities are updated after encoding / decoding each M-ary symbol. For example, when M=4, the array of cumulative distribution functions includes [c0, c1, c2, c3].

[0079] In some embodiments, the update of the M probabilities is based on the following formula:

number

[0080] In some embodiments, the M-ary arithmetic coding process may follow a conventional arithmetic coding engine design, but only the most significant 9 bits of the 15-bit probability value are input to the arithmetic encoder / decoder. The probability update rate α associated with a symbol is calculated based on the number of occurrences of the associated symbol when parsing the bitstream, and the value of α is reset at the beginning of a frame or tile using the following formula:

[0081] As an example,

number

[0082] Updating the rate α can lead to a strongly biased distribution where certain symbol probabilities are reduced to near zero. Probabilities close to zero can result in BD rate losses. To combat this effect, a regularization approach can be used, where the probability (p m ) is the threshold (P thr At the end of each probability update where p m P thr A regularization term is applied to all probabilities such that they are driven to . The regularization term may be taken from a uniform distribution and may depend on the sample space of the syntax element.

[0083] 5A-5B are diagrams illustrating an example approach to enforcing a minimum probability, according to some embodiments. As an example, in AV1, the minimum probability P minis applied to guard the probabilities fed to the arithmetic coding (sometimes referred to as the "minimal guard" approach), as shown in FIG. 5A. In the minimal guard approach shown in FIG. 5A, the subsequent model update increases p2 at stage n, which pushes p1 further towards 0, which could potentially lead to a loss of coding efficiency in the presence of model error.

[0084] As an alternative to the minimum guard approach, regularization can be used, as shown in FIG. 5B. For example, at the end of the update, P min Probability of falling below, say, p m Assuming that we have , we can apply a uniform distribution as a regularization term to adjust all probabilities simultaneously.

[0085] The CDF of the M-value uniform distribution is

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[0086] 6 is a flow diagram illustrating a method 600 for coding video in accordance with some embodiments. Method 600 may be performed in a computing system (e.g., server system 112, source device 102, or electronic device 120) having control circuitry and memory storing instructions for execution by the control circuitry. In some embodiments, method 600 is performed by executing instructions stored in a memory (e.g., memory 314) of the computing system.

[0087] The system obtains (602) video data having a plurality of syntax elements, the plurality of syntax elements including a first syntax element having a corresponding alphabet of M elements. For example, the system obtains the video data from a communication channel, such as channel 218. The system obtains (604) respective occurrence probabilities for the M elements of the first syntax element. For example, the system obtains the respective probabilities from picture memory 352, or generates the respective probabilities, or obtains the respective probabilities from a remote device (e.g., via channel 218). The system entropy codes (606) a first portion of the video data according to the respective occurrence probabilities. For example, the system encodes the first portion using entropy coder 214 and / or decodes the first portion using parser 254. While entropy coding the first portion of the video data, the system encounters (608) a first syntax element (e.g., coding module 320 encounters the first syntax element). For example, the first syntax element has a particular element from the M elements. The system updates (610) the occurrence probabilities for the M elements according to the first syntax element (e.g., using the coding module 320). For example, the system increases the occurrence probabilities for the particular element of the instance and decreases the occurrence probabilities for the other elements. In accordance with at least one of the updated probabilities for the M elements being less than the threshold probability value (612), the system determines (614) regularized occurrence probabilities for the M elements by applying a probability regularization to the updated occurrence probabilities (e.g., using the coding module 320), where the probability regularization does not include a division operation. In accordance with at least one of the updated probabilities for the M elements being less than the threshold probability value (612), the system entropy codes (616) a subsequent portion of the video data according to the regularized occurrence probabilities (e.g., using the coding module 320).If each of the updated probabilities for the M elements is greater than or equal to the threshold probability value, the system entropy codes (618) a second portion of the video data in accordance with the updated occurrence probabilities (e.g., using coding module 320).

[0088] In some embodiments, the minimum probability value P thr is predetermined, and when updating probabilities during entropy coding, after encoding or decoding the syntax R, the candidate probability update is tested, and the candidate probability update is determined to be at least one

number

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[0089] The inverse probability update rate β may be calculated as shown in Equation 1 below:

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[0090] The CDF entries can be adjusted as shown in Equation 3 below:

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[0091] In some embodiments, P thr If a lower probability is identified, the entries in the CDF are scanned in a prescribed order to find P thr Entries associated with lower probabilities are further adjusted by an offset. In some embodiments, the offset is adjusted so that, after applying the offset to adjust the entries in the CDF, the associated probability is P thr is a value that is close to or equal to

[0092] In one example, P thr is defined as 128 / 32768, and for a syntax with four symbol values, after the probability update, the CDF is {100, 10000, 20000, 32768}, where the probabilities of the four symbols are {100 / 32768, (10000-100}) / 32768, (20000-10000) / 32768, (32768-20000) / 32768}. In this example, the system determines that the probability of the first symbol (100 / 32768) is P thr lower and adjust the probabilities to {128, 10000, 20000, 32768}. After adjustment, no symbols have an associated probability lower than 1 and the adjustment process is terminated.

[0093] In some embodiments, the predetermined scan starts from the first entry in the CDF and proceeds toward the last entry in the CDF. In some embodiments, the predetermined scan starts from the last entry in the CDF and proceeds toward the first entry in the CDF. In some embodiments, the predetermined scan starts from P thr Starting with the first CDF entry associated with a lower probability and working towards the last entry. thr Start with the first CDF entry associated with the lower probability and work your way towards the first entry.

[0094] 6 depicts some logical stages in a particular order, stages that are not order dependent may be reordered and other stages may be combined or broken down. Any reordering or other grouping not specifically mentioned will be apparent to one of ordinary skill in the art, and the ordering and groupings presented herein are not exhaustive. It should also be recognized that the various stages may be implemented in hardware, firmware, software, or any combination thereof.

[0095] Now, referring to some example embodiments, in the following, R is a symbol space ε[s0,s1,...,s k ,…,s M ], probability ε[p0,p1,…,p k ,…,p M ], where M can take on values ​​ranging from, but not limited to, 2 to 16, and k≦M.

[0096] (A1) In one aspect, some embodiments include a method of video coding (e.g., method 600). In some embodiments, the method is performed in a computing system (e.g., server system 112) having memory and control circuitry. In some embodiments, the method is performed in a coding module (e.g., coding module 320). In some embodiments, the method is performed in an entropy coder (e.g., entropy coder 214). In some embodiments, the method is performed in a parser (e.g., parser 254). The method includes (i) obtaining video data having a plurality of syntax elements, the plurality of syntax elements including a first syntax element having a corresponding alphabet of M elements; (ii) obtaining respective probabilities of occurrence for the M elements of the first syntax element; (iii) entropy coding a first portion of the video data according to the respective probabilities of occurrence; (iv) while entropy coding the first portion of the video data, encountering the first syntax element; (v) updating the probabilities of occurrence for the M elements according to the first syntax element; and (vi) determining whether at least one of the updated probabilities for the M elements satisfies a threshold probability value (e.g., P thr (a) determining regularized probabilities of occurrence for the M elements by applying probability regularization to the updated probabilities of occurrence, where the probability regularization does not include a division operation, (b) entropy coding the second portion of the video data in accordance with the regularized probabilities of occurrence, and (vii) entropy coding the second portion of the video data in accordance with the updated probabilities of occurrence, where each of the updated probabilities for the M elements is greater than or equal to the threshold probability value.

[0097] For example, the entropy coder is or includes an adaptive arithmetic coder that updates probabilities after each instance of a syntax element is encountered / coded. For example, a first instance of a syntax element is encountered during the coding process. If the first instance of the syntax element is s1, then the probability (p1) associated with s1 is increased and the probabilities associated with other elements (e.g., s0 and s2) are decreased. As the coding process continues, a second instance of the syntax element is encountered. If the second instance of the syntax element is s0, then the probability associated with s0 is increased accordingly. In some embodiments, the probabilities are adapted by recursive scaling, with an update factor based on the alphabet size.

[0098] (A2) In some embodiments of A1, the number of M elements is in the range of 2 to 16. In some embodiments, the number of M elements is greater than 16. In some embodiments, the range is predetermined based on a coding protocol, standard, and / or configuration.

[0099] (A3) In some embodiments of A1 or A2, the probability of occurrence of each of the M elements is represented by a cumulative distribution function, such as the CDF described above with respect to FIG. 5B and FIG.

[0100] (A4) In some embodiments of any of A1-A3, each probability in the regularized occurrence probabilities for the M elements is greater than or equal to a threshold probability value. In some embodiments, the regularization process is performed such that each occurrence probability is greater than or equal to a threshold probability value (e.g., each probability P thr The present invention is configured to ensure that the above conditions are met.

[0101] (A5) In some embodiments of any of A1-A4, the threshold probability value is selected from a set of threshold probability values ​​based on one or more properties of the first syntax element. For example, the threshold probability value may be based on a number of the M elements.

[0102] (A6) In some embodiments of any of A1-A5, determining the regularized occurrence probabilities for the M elements includes determining an inverse probability update rate, such as the inverse probability update rate shown in Equation 2 above.

[0103] (A7) In some embodiments of A6, (i) the inverse probability update rate is determined by multiplying a first predetermined value by the output of a function, (ii) the first predetermined value is based on a number of symbol values ​​for the first syntax element, and (iii) the function is based on a threshold probability value and an updated probability value among the updated probabilities for the M elements that is less than the threshold probability value.

[0104] (A8) In some embodiments of A7, the function accesses a lookup table, and the threshold probability value and the value of the updated probability that is less than the threshold probability value are used to index the lookup table.

[0105] (A9) In some embodiments of A7 or A8, the output of the function is a positive integer (eg, 1, 2, ..., N).

[0106] (A10) In some embodiments of any of A7-A9, multiplying the first predetermined value by the output of the function includes performing a right shift operation (eg, as described above with respect to Equation 2).

[0107] (A11) In some embodiments of any of A1 to A10, determining the regularized occurrence probabilities for the M elements includes determining a value for a regularized cumulative distribution function (CDF). For example, the value of the regularized CDF is updated according to Equation 4 above.

[0108] (A12) In some embodiments of A11, the value for the regularized CDF is determined by multiplying the inverse probability update rate by a second predetermined value, the second predetermined value being based on a number of symbol values ​​for the first syntax element.

[0109] (A13) In some embodiments of A11, a value for the regularized CDF is determined by multiplying the inverse probability update rate by a second predetermined value and the CDF of the occurrence probabilities of each of the M elements.

[0110] (A14) In some embodiments of any of A1-A13, applying probability regularization to the updated occurrence probabilities includes scanning entries of a CDF of each occurrence probability for the M elements in a predetermined order. In some embodiments, the CDF is updated and then tested by scanning entries of the updated CDF in a predetermined order.

[0111] (A15) In some embodiments of A14, the scanning is terminated according to the scanned updated occurrence probability being greater than or equal to a threshold probability value.

[0112] (A16) In some embodiments of A14 or A15, the predetermined order is from a first entry of the CDF to a last entry of the CDF, or from a last entry of the CDF to a first entry of the CDF.

[0113] (A17) In some embodiments of A14, the predetermined order begins with entries of the CDF that have a probability of occurrence less than a threshold probability value.

[0114] (A18) In some embodiments of any of A1 to A17, applying probability regularization to the updated occurrence probabilities includes applying an offset to values ​​of the updated probabilities for the M elements that are less than the threshold probability value.

[0115] (A19) In some embodiments of A18, after applying the offset to the updated probability value, the updated probability value is greater than or equal to the threshold probability value.

[0116] (A20) In some embodiments of A18 or A19, the offset is selected such that the updated probability value is lower than the probability value of the second element of the M elements. For example, when updating the probabilities of individual hypotheses during entropy coding of syntax R, the probability update may be

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[0117] (A21) In some embodiments of any of A1 to A20, the second portion is entropy coded according to a regularized probability of occurrence pursuant to a determination that M is less than a threshold number. For example, probability regularization is performed only on syntax elements having less than a preset threshold number of elements (e.g., less than 12, 10, 8, 6, 4, or 2). In this example, the system forgoes applying the regularization operation to syntax elements having more than a preset threshold number of elements.

[0118] (B1) In another aspect, some embodiments include a method of video coding. In some embodiments, the method is performed in a computing system (e.g., server system 112) having memory and control circuitry. In some embodiments, the method is performed in a coding module (e.g., coding module 320). In some embodiments, the method is performed in an entropy coder (e.g., entropy coder 214). In some embodiments, the method is performed in a parser (e.g., parser 254). The method includes (i) obtaining video data having a plurality of syntax elements, the plurality of syntax elements including a first syntax element having a corresponding alphabet of M elements; (ii) obtaining respective probabilities of occurrence for the M elements of the first syntax element; (iii) entropy coding a first portion of the video data in accordance with the respective probabilities of occurrence; (iv) encountering the first syntax element while entropy coding the first portion of the video data; (v) updating the probabilities of occurrence for the M elements in accordance with the first syntax element; (vi) entropy coding a second portion of the video data in accordance with the respective probabilities of occurrence according to at least one of the updated probabilities for the M elements being less than a threshold probability value; and (vii) entropy coding the second portion of the video data in accordance with the updated probabilities of occurrence according to each of the updated probabilities for the M elements being greater than or equal to the threshold probability value.

[0119] In some embodiments, the minimum probability value P thr is predetermined, and when updating probabilities during entropy coding, after encoding or decoding the syntax R, the candidate probability update is tested, and the candidate probability update is determined to be at least one

number

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[0120] (B2) In some embodiments of B1, the number of M elements is in the range of 2 to 16. In some embodiments, the number of M elements is greater than 16. In some embodiments, the range is predetermined based on a coding protocol, standard, and / or configuration.

[0121] (B3) In some embodiments of B1 or B2, the probability of occurrence of each of the M elements is represented by a cumulative distribution function, such as the CDF described above with respect to FIG. 5B and FIG.

[0122] (B4) In some embodiments of any of B1-B3, the threshold probability value is selected from a set of threshold probability values ​​based on one or more properties of the first syntax element. For example, the threshold probability value may be based on a number of the M elements.

[0123] (B5) In some embodiments of any of A1-B4, the second portion is entropy coded according to the respective probabilities of occurrence pursuant to a determination that M is less than a threshold number. For example, determining whether to use the updated probabilities may be based on whether the first syntax element has less than a pre-set threshold number of elements (e.g., less than 12, 10, 8, 6, 4, or 2).

[0124] The methods described herein may be used separately or combined in any order. Each of these methods may be implemented by a processing circuit (e.g., one or more processors or one or more integrated circuits). In some embodiments, the processing circuit executes a program stored on a non-transitory computer-readable medium.

[0125] In some embodiments, the term "block" may be interpreted as a prediction block, a coding block, or a coding unit (CU). In some embodiments, the term "block" is used to refer to a transform block. In some embodiments, the term "block size" refers to either the block width or height, the maximum width and height, the minimum width and height, the area size (width x height), and / or the aspect ratio of the block (width:height or height:width). In some embodiments, a faster update rate refers to a larger value of the update rate and / or a smaller probability update window size. In some embodiments, a slower update rate refers to a smaller value of the update rate and / or a larger probability update window size.

[0126] In another aspect, some embodiments include a computing system (e.g., server system 112) including control circuitry (e.g., control circuitry 302) and a memory (e.g., memory 314) coupled to the control circuitry, the memory storing one or more instruction sets configured to be executed by the control circuitry, the one or more instruction sets including instructions for performing any of the methods described herein (e.g., A1-A21 and B1-B5 above).

[0127] In yet another aspect, some embodiments include a non-transitory computer-readable storage medium having stored thereon one or more instruction sets for execution by control circuitry of a computing system, the one or more instruction sets including instructions for performing any of the methods described herein (e.g., A1-A21 and B1-B5 above).

[0128] It is to be understood that although the terms "first," "second," etc. may be used herein to describe various elements, the elements should not be limited by these terms, and these terms are used only to distinguish one element from another.

[0129] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the claims. As used in the description of the embodiments and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It is also to be understood that the term "and / or," as used herein, refers to and includes any and all possible combinations of one or more of the associated listed items. It is further to be understood that the terms "comprise" and / or "comprising," as used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0130] As used herein, the term "if" may be interpreted to mean "when" or "response thereto" or "response to determining" or "pursuant to determining" or "response to detecting" the stated precondition is true, depending on the context. Similarly, the phrases "if it is determined that [the stated precondition is true]" or "if [the stated precondition is true]" or "when [the stated precondition is true]" may be interpreted to mean "response to determining" or "response to determining" or "pursuant to determining" or "response to detecting" or "response to detecting" the stated precondition is true, depending on the context.

[0131] The foregoing description has been described with reference to specific embodiments for purposes of explanation. However, the exemplary description above is not intended to be exhaustive or to limit the claims to the precise forms disclosed. Numerous modifications and variations are possible in light of the above teachings. These embodiments have been selected and described in order to best explain the principles of operation and practical application, thereby enabling others skilled in the art.

Claims

1. 1. A method of video coding executed by a computing system having memory and control circuitry, comprising: obtaining video data having a plurality of syntax elements, the plurality of syntax elements including a first syntax element having a corresponding alphabet of M elements; obtaining respective occurrence probabilities for the M elements of the first syntax element; entropy coding a first portion of the video data in accordance with the respective probabilities of occurrence; encountering the first syntax element while entropy coding the first portion of the video data; updating occurrence probabilities for the M elements according to the first syntax element; pursuant to at least one of the updated occurrence probabilities for the M elements being less than a threshold probability value; determining regularized occurrence probabilities for the M elements by applying probability regularization to the updated occurrence probabilities, the probability regularization not including a division operation; entropy coding a second portion of the video data in accordance with the regularized probability of occurrence; entropy coding the second portion of the video data in accordance with the updated probabilities of occurrence for the M elements, each of the updated probabilities of occurrence being greater than or equal to the threshold probability value; The method according to claim 1,

2. The method of claim 1 , wherein the threshold probability value is selected from a set of threshold probability values ​​based on a number M of the M elements.

3. The method of claim 1 , wherein determining the regularized occurrence probabilities for the M elements comprises determining an inverse probability update rate.

4. the inverse probability update rate is determined by multiplying a first predetermined value by an output of a function; the first predetermined value is based on a number of symbol values ​​for the first syntax element; the function is based on the threshold probability value and an updated probability of occurrence value among the updated probabilities of occurrence for the M elements that is less than the threshold probability value. The method according to claim 3.

5. 5. The method of claim 4, wherein the function comprises accessing a lookup table, and the threshold probability value and the value of the updated probability of occurrence that is less than the threshold probability value are used to index the lookup table.

6. 5. The method of claim 4, wherein multiplying the first predetermined value by the output of the function comprises performing a right shift operation.

7. The method of claim 1 , wherein determining the regularized probabilities of occurrence for the M elements comprises determining a value for a regularized cumulative distribution function (CDF).

8. 8. The method of claim 7, wherein the value for the regularized CDF is determined by multiplying an inverse probability update rate by a second predetermined value and a CDF of the respective occurrence probabilities for the M elements.

9. 2. The method of claim 1, wherein applying the probability regularization to the updated occurrence probabilities comprises scanning entries of a CDF of the respective occurrence probabilities for the M elements in a predetermined order.

10. 10. The method of claim 9, wherein the predetermined order is from a first entry of the CDF to a last entry of the CDF, or from the last entry of the CDF to the first entry of the CDF.

11. 10. The method of claim 9, wherein the predetermined order begins with entries of the CDF that have a probability of occurrence less than the threshold probability value.

12. 2. The method of claim 1 , wherein applying the probability regularization to the updated occurrence probabilities comprises applying an offset to values ​​of the updated occurrence probabilities for the M elements that are less than the threshold probability value.

13. The method of claim 1, wherein the threshold probability value is determined in advance.

14. A control circuit; a memory storing one or more instruction sets; Including, The one or more sets of instructions, when executed by the control circuitry, cause the control circuitry to perform a method according to any one of claims 1 to 13. Computing system.

15. A computer program causing a computer to carry out the method according to any one of claims 1 to 13.

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