306 results about "Arithmetic coding" patented technology

A system and method for cross-domain knowledge transfer in federated compression networks. The system enables efficient lossless data compression across diverse data types by intelligently sharing compression strategies between domains. A cross-domain knowledge transfer system identifies relationships between different data domains, adapts compression parameters accordingly, and optimizes learning processes to maximize knowledge reuse. The architecture may include a knowledge repository for storing domain features and compression patterns, domain mapping components that identify similarities, and transfer learning optimization that enables efficient adaptation with minimal examples. This approach significantly accelerates model training for new domains while improving compression performance. Applications include satellite telemetry systems where efficient compression is critical for transmitting large information sets between distant locations. The system may employ probability prediction driven arithmetic coding paired with long short-term memory networks, enhanced by cross-domain knowledge sharing that adapts successful compression strategies from one domain to another while preserving domain-specific optimization.

The invention relates to a multi-dimensional transmission data compression sensing method and system for urban emergency rescue, and the method comprises the steps: obtaining multi-modal data, carrying out the normalization processing and sparse representation, and obtaining the sparse coefficient of each modal; constructing a block diagonal random matrix for each modal sparse coefficient to perform independent compression sampling, generating a low-dimensional observation value before coding, and performing arithmetic coding and low-density parity check code error correction coding to generate an anti-interference code stream; and performing low-density parity check code decoding and arithmetic decoding on the anti-interference code stream to obtain a decoded low-dimensional observation value, performing iteration by using an orthogonal matching pursuit algorithm, recovering sparse coefficients of each mode, performing reconstruction to obtain text, image and audio features, and projecting the text, image and audio features to a shared semantic space to obtain a shared semantic space. And calculating a joint semantic weight through a cross-modal attention mechanism, and generating a multi-modal fusion result with consistent semantics. The method disclosed by the invention provides an efficient, robust and semantic collaborative end-to-end solution for urban emergency rescue.

A video encoder is configured to entropy encode an absolute value of a quantization level of a current transform coefficient at position (xC, yC), wherein the absolute value is encoded using context adaptive binary arithmetic encoding of bins of a first binarization. The video coder is further configured, for the current transform coefficient, to encode a bin of the first binarization by using a context which is determined based on a sum of minimum absolute values of transform coefficient quantization levels, based on encoded bins of the first binarization, at one or more transform coefficient positions among (xC+1, yC), (xC+2, yC), (xC+1, yC+1), (xC, yC+1), and (xC, yC+2).

The invention discloses a point cloud compression method and device based on a multi-scale octree attention mechanism, and relates to the field of image processing, and the method comprises the steps: an encoder network receives point cloud data, carries out the down-sampling and feature extraction of a point cloud through a downscaling feature extractor, obtains a downscaled deep feature point cloud, and carries out the feature extraction of the point cloud; the method comprises the following steps of: firstly, encoding the data into an octree in a recursive manner, constructing a context window according to a relationship among octree nodes, introducing a multi-head attention mechanism to perform feature fusion on the octree nodes to obtain an occupancy probability of the octree nodes, and compressing the occupancy probability into a bit stream by using arithmetic encoding; and the decoder network decompresses the bit stream to obtain a reconstructed point cloud, upsampling and feature reconstruction are performed on the reconstructed point cloud by using an upscaling feature reconstruction device, and finally a reconstructed point cloud with the same resolution as the initial point cloud is obtained. According to the invention, on the premise of ensuring the quality of the same point cloud, the point cloud compression efficiency is effectively improved, and the bit overhead is reduced.

The invention relates to probability estimation in multi-symbol entropy coding. Entropy coding, such as multi-symbol arithmetic coding, is used for video compression to encode data into a compressed bitstream for transmission. Some entropy coding techniques are adaptive, which means that the probability distribution is updated instantly based on data. Accuracy of cumulative probability estimation in adaptive multi-symbol arithmetic coding may affect coding efficiency. To solve this problem, a mixture of two or more adaptive cumulative probability estimates calculated using two or more adaptation parameters may be used in place of a single cumulative probability estimate. The two or more adaptation parameters may be unique to the context model. The divergence in the adaptive cumulative probability estimation may represent a sudden change in the probability of the symbol. The divergence may trigger a reset of one or more adaptive cumulative probability estimates.

One example method includes receiving, by a large language model (LLM), input text to be compressed, defining a size of a rolling window of previous tokens, generated prior to receipt of the input text, that the LLM is permitted to consider in a conditional probability estimate, generating, by the LLM, tokenized text based on the input text, and the tokenized text comprises a sequence of tokens, based on the previous tokens, obtaining a probability mass function of a next token of the sequence, providing the probability mass function as an input to an arithmetic coding (AC) scheme, and assigning, by the AC scheme, a respective binary code to the token with a highest probability as assigned by the LLM.

The invention provides a video semantic transmission method based on priority division, and the method comprises the steps: obtaining an image group corresponding to a to-be-transmitted video, carrying out the feature extraction based on multiple tasks, and obtaining the motion vector feature, background feature and object feature of the to-be-transmitted video; next, feature priority division is carried out, the divided features are screened according to a dynamic feature screening threshold to obtain fusion features, priority weights corresponding to the fusion features are subjected to mapping processing to obtain probability distribution, arithmetic coding and arithmetic decoding are carried out on the fusion features according to the probability distribution to obtain corresponding video semantic features; and finally, performing semantic decoding processing, and reconstructing an image group obtained by decoding to obtain a transmitted video. Through the method and the device, the technical problems of loss of important data feature information and low quality of subsequent video recovery and reconstruction due to adoption of segmentation transmission of information source information during semantic communication in the prior art are solved.

A method performed by at least one processor of a video decoder includes receiving a coded video bitstream including at least one picture and one or more syntax elements encoded in accordance with multi-hypothesis arithmetic coding. The method further includes decoding each syntax element from the one or more syntax elements based on the multi-hypothesis arithmetic coding. The method further includes selecting a probability update rate from a plurality of probability update rates based on a predetermined condition, the plurality of probability update rates including a first probability update rate that is higher than a second probability update rate. The method further includes updating at least one probability model utilized in the multi-hypothesis arithmetic coding based on the selected probability update rate. The method further includes decoding at least one block in the at least one picture based on the decoded one or more syntax elements.

This disclosure provides methods, devices and systems for encoding data, to achieve a symbol distribution, for wireless communication. One implementation includes a method in which arithmetic coding (AC) encoding is constrained by a set of one or more target compositions for symbol sequences. The target compositions are known, and the encoding method is performed in multiple iterations. Each iteration generates a symbol and establishes a composition prefix, which is taken into account in the subsequent iteration. The methods generate output sequences defining symbols that are used to encode data for transmission.

In one implementation, a method of encoding or decoding point cloud data is provided, comprising: obtaining a feature map representing attributes of voxels in an octree structure; determining one or more probability distribution parameters for a probability density function associated with an attribute of a current voxel, based on the feature map; determining a probability mass function of the attribute of the current voxel based on the one or more probability distribution parameters for the probability density function for the current voxel; and encoding or decoding attribute information of the current voxel in the octree structure, based on the probability mass function of the attribute for the current voxel.

A system and method for federated two-stage compression with federated joint learning. The system and method proposed allow for fast and efficient lossless data compression of a large variety of data types. The system and method have a variety of real-world applications, including deep learning solutions for telemetry, tracking, and command subsystems for satellites. Satellites and their control centers are incredibly spaced apart which makes data compression an extremely important process to transmit large sets of information in a low-latency, high-efficiency environment. The proposed system and method utilize probability prediction driven arithmetic coding which provides faster encoding times and higher compression ratios when paired with a long short-term memory system for data compression.

The invention is suitable for the technical field of image processing, and provides an FPGA-based cache-free real-time image compression transmission method and system, and the method comprises the steps: sequentially carrying out the block processing, level translation processing and component transformation processing of image data, and obtaining a preprocessed image; carrying out discrete wavelet transform processing on the preprocessed image to obtain a wavelet output result, and storing the wavelet output result in an FIFO (First In First Out) memory; for the wavelet output result, obtaining context information and decision bit information by adopting a bit-plane coding method of four-channel parallel and all-bit-plane parallel processing; carrying out arithmetic coding on the context information and the decision bit information by adopting a multi-stage pipeline processing method to obtain a compressed code stream; and converting the compressed code stream into a standardized code stream format. According to the method, the memory resource demand can be effectively reduced, the delay is reduced, and the real-time image compression requirement is met.

The invention relates to a task-oriented semantic communication-oriented adaptive source channel coding system, which belongs to the field of wireless communication, and comprises a sending end for extracting a semantic feature map for evaluation from input data through a feature extractor initialized based on a pre-training large model, executing nested quantization and arithmetic coding based on a calculated importance score, and sending the semantic feature map to a task-oriented semantic communication-oriented adaptive source channel coding system; generating a scalable semantic bit stream with importance levels; the physical layer is used for carrying out reordering and grouping according to importance levels of bit streams, a channel encoder is combined with an interleaver to realize unequal error protection of semantic matching, and encoded bits are mapped to sign bits with different fault-tolerant capabilities in a constellation diagram through division modulation; and a receiving end: recovering the semantic feature map through arithmetic decoding and nested inverse quantization. According to the invention, on the premise of keeping compatibility with a digital communication protocol stack, through distortion-driven joint rate self-adaption, the transmission effectiveness for machine tasks and human vision is obviously improved under a limited bandwidth.

A method and an apparatus including processing circuitry are provided. The processing circuitry determines previous probability information associated with each entropy coded region of multiple regions in a previous picture. The processing circuitry selects, based on (i) a location or a quantization parameter of an independently decodable coding segment in a current picture or (ii) syntax information of the independently decodable coding segment, a region among the multiple regions. Initial probability information for one or more current syntax elements of a block in the independently decodable coding segment is determined based on the previous probability information associated with the selected region. The one or more current syntax elements are first to be entropy decoded in the independently decodable coding segment. The processing circuitry entropy decodes coded bits associated with the one or more current syntax elements into a bin string based on the initial probability information.

Devices, systems, and methods for digital video coding, which includes matrix-based intra prediction methods for video coding, are described. In a representative aspect, a method for video processing includes encoding a current video block of a video using a matrix intra prediction (MIP) mode in which a prediction block of the current video block is determined by performing, on previously coded samples of the video, a boundary downsampling operation, followed by a matrix vector multiplication operation, and selectively followed by an upsampling operation; and adding, to a coded representation of the current video block, a syntax element indicative of applicability of the MIP mode to the current video block using arithmetic coding in which a context for the syntax element is derived based on a rule.

A device may obtain a first value for a first binarization symbol associated with video data and a second value for a second binarization symbol associated with the video data. The device may obtain a probability value associated with a third binarization symbol associated with the video data based on the first value, the second value, and a probability value associated with the first binarization symbol. The device may then decode the video data based on the probability value associated with the third binarization symbol. The first, second and third binarization symbols may be for a transform coefficient. In examples, the first, second and third binarization symbols may be associated with a context for entropy decoding. For example, the first, second and third binarization symbols may be associated with an entropy decoding context for decoding the video data using context-based adaptive binary arithmetic coding (CABAC).

An encoder includes circuitry and memory coupled to the circuitry. The circuitry, in operation, for each coefficient of a plurality of coefficients included in a block, determines a base level relating to Context-Based Adaptive Binary Arithmetic Coding (CABAC) for the coefficient, and encodes an absolute value of the coefficient. In determining the base level, when one or more flags are used in encoding the absolute value of the coefficient, the base level is determined to be a first value, and when one or more flags are not used in the encoding, the base level is determined to be a second value that is smaller than the first value. In encoding the absolute value of the coefficient, when one or more flags are not used, a rice parameter is determined based on the base level which is equal to the second value, and the coefficient is binarized using the rice parameter.

The invention relates to the technical field of computers, and provides a potential space compression method, a potential space decompression method, a potential space compression device, a potential space decompression device, potential space compression equipment and a potential space decompression program product. Compressing the first potential variable through a neural network compression model to obtain a compressed second potential variable, and compressing the first potential variable through a neural network down-sampling model to obtain a down-sampled first potential variable; the arithmetic coding model is used for carrying out lossless Gaussian arithmetic coding on the down-sampled first potential variable to obtain a coded second potential variable; and the compressed second potential variable is transmitted to a decoding end, so that the decoding end decodes the second potential variable to obtain a decoded target image, the structural information of the data can be effectively utilized, efficient lossless compression can be realized, the first potential variable can be compressed more efficiently, the compression ratio of the image data is further improved, and the compression efficiency of the image data is improved. And image data compression cost is reduced.

The invention relates to the technical field of industrial data compression, in particular to an industrial operation and maintenance data hybrid compression storage method, system and device and a medium. High compression rate and lossless storage are realized by distinguishing time sequence data from non-time sequence feature vectors and respectively adopting Huffman coding and LLM-driven arithmetic coding; and through efficient compression processing, especially effective reduction of feature vector redundancy, the space required by data storage is greatly reduced, so that the storage cost of the operation and maintenance data of the generic semiconductor industrial equipment is reduced.

Methods, apparatus, and computer readable storage medium for multi-symbol arithmetic coding in video decoding. The method includes receiving a coded video bitstream; obtaining an array of cumulative distribution functions and corresponding M symbols, wherein M is an integer larger than 1; and performing, based on the array of cumulative distribution functions, arithmetic decoding on the coded video bitstream to extract at least one symbol by: for each extracted symbol, updating the array of cumulative distribution functions according to the extracted symbol based on at least one probability update rate, and continuing, based on the updated array of cumulative distribution functions, arithmetic decoding on the coded video bitstream to extract next symbol.

The invention relates to a JBIG arithmetic coding and decoding method and system, the method is realized based on a system structure of a QM encoder and a decoder, the QM encoder comprises a self-adaptive coding module and a coding unit, and the decoder comprises a self-adaptive decoding module and a decoding unit; the method comprises the following steps: step 1) generating a context CX; step 2) performing a JBIG arithmetic coding process; and step 3) performing a JBIG arithmetic decoding process. According to the JBIG arithmetic coding and decoding method and system, the throughput of an engine is improved, the problem of data dependence conflicts in an assembly line is solved, images can be processed at the speed close to one pixel in each clock period, the processing speed is high, the performance can be improved by about 40%, the image compression and processing efficiency is improved, compatibility is high, and the method and system are suitable for popularization and application. And interaction and communication with other JBIG compatible equipment can be realized.

The invention relates to the technical field of point cloud, in particular to a coding and decoding method for point cloud compression. The invention provides a coding method for geometric compression of a point cloud, which comprises the following steps of: performing layer-by-layer down-sampling and layer-by-layer up-sampling on each spatial scale of a point cloud group, and training a network through over-fitting to obtain optimized network parameters; based on the network parameters, performing layer-by-layer up-sampling on each spatial scale of the point cloud group, predicting the occupancy probability of the child nodes and taking the occupancy probability as a code table, performing arithmetic coding on occupancy codes of the child nodes, and generating an occupancy code stream; and coding the network parameters to generate a network parameter code stream. According to the invention, the adjacent frames with similar features in the point cloud sequence share the lightweight network parameters for coding and decoding, so that the repeated transmission of the network parameters is reduced, and the average bandwidth consumption of the network parameters in the transmission process is reduced.

The invention discloses a high-definition video low-delay compression method based on self-adaptive adjustment, and aims to solve the problems of insufficient self-adaptive adjustment capability, too high encoding and decoding delay and low code rate and network bandwidth matching degree in the existing high-definition video compression technology. The method comprises the following steps: firstly, acquiring a high-definition video stream and a real-time network bandwidth parameter, extracting intra-frame texture complexity, inter-frame motion intensity and scene switching frequency characteristics, and constructing a two-dimensional adaptive compression strategy in combination with a real-time bandwidth; low-delay coding is executed by adopting parallel frame fragmentation and simplified adaptive arithmetic coding, adaptive code rate control is realized by combining code rate overflow early warning and intra-frame key region priority bit allocation, and finally, fast inverse transformation, quantization recovery and motion compensation optimization are completed at a decoding end based on strategy parameters synchronously transmitted at a coding end so as to reconstruct a high-definition video frame. According to the invention, the adaptive adjustment capability of video compression is improved, low time delay of coding and decoding is realized, and the method is suitable for real-time high-definition video transmission scenes such as remote monitoring and video conferences.

An encoder includes circuitry and memory coupled to the circuitry. In residual coding of a current block to which an orthogonal transform is not applied, when coefficient information flags relating to a coefficient in the current block are encoded, the circuitry: performs a level mapping process to transform the coefficient to a second coefficient by using a predicted value, in which the predicted value is determined based on neighboring coefficients of the coefficient within the current block; encodes second coefficient information flags by Context-based Adaptive Binary Arithmetic Coding (CABAC), each of the second coefficient information flags relating to the second coefficient; and encodes a remainder value of the coefficient with Golomb-Rice code, and when the coefficient information flags are not encoded, in operation, the circuitry: skips the level mapping process; and encodes a value of the coefficient with the Golomb-Rice code.

Entropy coding a sequence of syntax elements is described where an observation for a syntax element of the sequence is determined, and the observation is arithmetic coded using the probability model. Thereafter, the probability model is updated using a time-variant update rate to produce an updated probability model. Updating the probability model includes regularizing one or more probability values of the probability model so no probability of the updated probability model is below a defined minimum resolution. As a result, the use of a minimum probability value during the arithmetic coding, which can distort probability model, may be omitted.

The invention provides a reversible hiding method and system for a high-capacity image ciphertext domain, and belongs to the technical field of image ciphertext information hiding. A plaintext image is encrypted through two stages of coarse-grained encryption and fine-grained encryption; preprocessing the encrypted plaintext image, and determining whether a sub-block is an overflow block or a valid block; for the non-overlapped effective sub-blocks, using the median coefficients of the sub-blocks to predict the maximum and minimum coefficients and the secondary maximum and minimum coefficients so as to realize histogram construction; expanding by using a high-frequency coefficient, and modifying a prediction error; and expanding the encrypted secret information, the length of the position map, the position map subjected to arithmetic coding compression and an end flag bit to realize information embedding. According to the method, larger image blocks are considered, and the maximum and minimum values and the secondary maximum and minimum values are predicted by using the median, so that more coefficients participate in the embedding process, and the upper limit of the pixel utilization rate is improved; and based on the histogram modification method of optimization mapping, the high-frequency coefficient prediction error is fully utilized, and the embedding capacity is further improved.

To provide a data compression system that combines large-scale language models (LLMs) with distributed computing to solve the problems that conventional compression techniques only consider statistical redundancy and are unable to exploit semantic structure or contextual information, and furthermore, large-scale model-based compression requires high resources and fails to fully exploit the interrelationships in multimodal data.SOLUTION: The present invention achieves highly efficient compression even in resource-constrained environments, by utilizing the interrelationships between different data formats using a multimodal understanding module, selecting an optimal model according to the data characteristics and communication environment using an adaptive model selection module, utilizing shared knowledge between terminals via a distributed collaborative compression module, transferring the compression capabilities of large-scale models using a knowledge distillation module to lightweight models, and integrating efficient coding using an adaptive arithmetic coding module.SELECTED DRAWING: None

System, methods, and instrumentalities are disclosed for video encoding / decoding. For example, a device for video encoding and / or decoding (e.g., a video encoder and / or a video decoder) may be configured for a spatial context-adaptive binary arithmetic coding (CABAC) tuning. The device may determine whether a current coding unit (CU) is located at the beginning of a current coding tree unit (CTU) in a scanning order. Based on a determination that the current CU is located at the beginning of the current CTU in a scanning order, the device may determine at least one neighboring sample that is present for the spatial CABAC tuning for video decoding and / or video encoding. The at least one neighboring sample may be associated with a neighboring CTU that is not located in the current CTU. The device may decode / encode the current CU based on the determined at least one neighboring sample.

An apparatus with a processor receives a bitstream including a syntax element indicating whether prediction errors, mesh connectivity information, and additional basemesh syntax elements are transmitted in a single entropy packet or a plurality of entropy packets, a first set of arithmetically coded prediction errors, and a second set of arithmetically coded prediction errors for decoding a mesh frame. The processor decodes the syntax element and arithmetically decodes the first and second set of arithmetically coded prediction errors based on the syntax element. In one example, the first and second set of arithmetically coded prediction errors are included in a single entropy packet if the syntax element has a first value and the first set of arithmetically coded prediction errors is in a first entropy packet and the second set of arithmetically coded error predictions is in a second entropy packet if the syntax element has a second value.

An encoding device (100) is provided with: a memory (152); and a circuit (151) capable of accessing the memory (152), the circuit (151), during operation, encodes a connection type pertaining to a connection relationship between a surface to be processed and an unprocessed surface by context-based arithmetic encoding for each of a plurality of surfaces constituting a three-dimensional grid, and, during encoding of a current connection type, which is the connection type to be encoded, encodes the current connection type to be encoded by context-based arithmetic encoding for each of the plurality of surfaces constituting the three-dimensional grid. The context to be applied to the arithmetic encoding is selected from a plurality of contexts using a previous connection type that is the connection type encoded prior to the current connection type.