73 results about "Residual coding" patented technology

To provide a method and apparatus for improving image coding efficiency.SOLUTION: An image decoding method includes the steps of: acquiring a sign data hiding enable flag; acquiring a transform skip residual coding (TSRC) enable flag based on the sign data hiding enable flag; acquiring residual information for a current block based on the TSRC enable flag; deriving a residual sample of the current block based on the residual information; and generating a reconstructed picture based on the residual sample. The sign data hiding enable flag is a flag indicating whether sign data hiding is enabled, the TSRC enable flag is a flag indicating whether TSRC is enabled, and the TSRC enable flag is acquired based on the sign data hiding enable flag having a value of zero.SELECTED DRAWING: Figure 10

A method of decoding an image according to a decoding apparatus of the present document includes the steps of obtaining a dependent quantization available flag regarding whether dependent quantization is available, obtaining a sign data hiding available flag regarding whether sign data hiding is available, and obtaining a transform skip residual coding (TSRC) available flag regarding whether TSRC is available based on the dependent quantization available flag and the sign data hiding available flag.

Methods, apparatuses, and non-transitory computer-readable storage mediums are provided for video encoding and decoding. An encoder may signal a control flag in a slice header level. The encoder may signal at least one syntax element in the slice header level. The control flag may be a residual coding disabled flag. The at least one syntax element may comprise a syntax element related to a residual coding rice index.

This invention provides a system and method for encoding and decoding video data. [Solution] The solution includes receiving a video frame for residual coding, determining whether the video frame is coded according to a first coding mode, and turning off sign data hiding for residual coding in response to determining whether the video frame is coded according to the first coding mode.

The application discloses a point cloud data processing method, system, device and medium of a humanoid robot. The method comprises the following steps: acquiring a motion state parameter of a robot and initial point cloud data collected; performing dynamic sampling processing on the robot according to the motion state parameter and the initial point cloud data, and generating a projection image; performing multi-channel feature extraction and dynamic weight fusion processing on the projection image, and obtaining an encoded feature map; performing multi-scale residual coding processing on the encoded feature map according to an information theory constraint, and obtaining encoded data; and performing reconstruction processing on the encoded data according to the motion state parameter, and obtaining reconstructed point cloud data. The embodiment of the application can improve the processing efficiency of point cloud data and can be widely applied to the technical field of intelligent robots.

A residual coding method is provided. The method comprises: when the current frame is an inter-frame prediction frame, determining whether a residual of a background region in the current frame needs to be compensated for; and when the residual of the background region in the current frame needs to be compensated for, coding first residual data, and when the residual of the background region in the current frame does not need to be compensated for, coding second residual data, wherein the first residual data is residual data of an entire image of the current frame, and the second residual data is residual data of a target region in the current frame. The present disclosure further provides a video coding method using the residual coding method, and corresponding devices and a storage medium.

The invention relates to an adaptive configuration method for compression parameters of ordered key learning. The adaptive configuration method comprises the following steps: selecting a public data set containing ordered integer keys; calculating a gap value between two adjacent integer keys so as to obtain a gap value sequence set between all the integer keys; all change point positions of the sequence set are calculated by adopting a Bayesian online change point detection algorithm and mapped back to the original data set, and the original data set is divided into a plurality of partitions with similar statistical characteristics by change points; setting an initial error upper limit threshold value of each partition, and constructing a piecewise linear function of each partition and a corresponding bit-level space total cost function; solving an optimal error upper limit and a corresponding residual bit width in combination with the partition variance and the partition constraint; constructing a configuration portrait library containing optimal configuration; and traversing all partitions, generating a compression parameter adaptive configuration table, constructing a learning compressor according to the compression parameter adaptive configuration table, performing error controlled prediction and residual encoding on an original sequence, and outputting a final compression result.

Image decoding method, image encoding method, and transmission method. An image decoding method implemented by a decoding apparatus according to the present document includes the steps of: obtaining prediction-related information of a current block; obtaining prediction-related information of a current block; obtaining a dependent quantization enabled flag related to whether dependent quantization is available; obtaining a transform skip residual coding (TSRC) enabled flag related to whether TSRC is available based on the dependent quantization enabled flag; obtaining residual information of a residual coding syntax of the current block derived based on the TSRC enabled flag; deriving motion information of the current block based on the prediction-related information; deriving prediction samples of the current block based on the motion information; deriving residual samples of the current block based on the residual information; and generating a reconstructed picture based on the prediction samples and the residual samples.

The invention provides an image decoding apparatus, an encoding apparatus, and an image information transmitting apparatus. A method for decoding an image by a decoding device according to the present document comprises the steps of: acquiring a dependent quantization availability flag regarding whether dependent quantization is available; obtaining a symbol data hiding available mark about whether symbol data hiding is available or not; and obtaining a transform skip residual coding (TSRC) available flag on whether TSRC is available based on the quantization dependent available flag and the symbol data hidden available flag.

Methods and apparatuses are provided for video coding with lossless coding modes. The method includes: determining whether a current block is in a transform skip mode; in response to determining that the current block is in the transform skip mode, determining whether a first residual coding scheme or a second residual coding scheme is selected for the current block in the transform skip mode; and signaling a first indication which indicates whether a current block is in the transform skip mode and signaling a second indication which indicates whether the first residual coding scheme or the second residual coding scheme is applied for blocks in the transform skip mode.

In a method of video decoding, a no transform skip residual coding rice constraint flag in a general constraint information (GCI) syntax structure for coded video data in a bitstream is determined. The no transform skip residual coding rice constraint flag is associated with a residual coding tool. When the no transform skip residual coding rice constraint flag in the GCI syntax structure is equal to 1, the coded video data is decoded without invoking the residual coding tool. When the no transform skip residual coding rice constraint flag is equal to 0, a value of a transform skip residual coding rice present in slice header flag for one of one or more coded layer video sequences (CLVSs) in the coded video data is determined. The coded video data in the bitstream is determined based on the value of the transform skip residual coding rice present in slice header flag.

The application relates to the technical field of data compression storage, and discloses a time series database driven monitoring data compression storage method, which comprises the following steps: S1, preprocessing multi-source monitoring data, and constructing a dynamic tensor containing a timestamp, a numerical index and a multi-dimensional label; S2, performing dynamic dimension reduction processing on the dynamic tensor to generate a core tensor and a multi-dimensional factor matrix; S3, based on the core tensor and the multi-dimensional factor matrix, determining compression parameters, decompression parallelism and index granularity through a joint optimization model; and S4, performing hierarchical coding on residual data generated by the dynamic dimension reduction processing to generate a light residual coding result. Through dynamic tensor decomposition and incremental updating technology, low storage overhead and real-time dimension expansion capability of streaming monitoring data are realized, the problems of calculation redundancy and storage expansion caused by the incapability of the streaming monitoring data to adapt to dynamic newly-added labels are solved, and the frequent reconstruction cost caused by dynamic expansion of the data is avoided.

An example method of encoding a point cloud includes determining that residual values of all but one component of an attribute of a point in the point cloud are equal to zero, determining, based on the determination that the residual values of all but the one component of the attribute are equal to zero, that a value of the one component is equal to a magnitude of a residual value of the one component of the attribute minus an offset, encoding the value of the one component, and signaling the encoded value in a bitstream.

Methods, devices, and non-transient, computer-readable storage media are provided for video decoding. In one method, a decoder receives a rice extension flag from the Sequence Parameter Set (SPS) indicating whether an extension of the rice parameter derivation for abs_remainder and dec_abs_level binarization is enabled. In a second method, the decoder can receive an enabled rice adaptation flag from the Sequence Parameter Set (SPS) indicating whether the rice parameter derivation for abs_remainder and dec_abs_level binarization is initialized at the beginning of each transform unit (TU) with accumulated statistics from previous TUs.

For a transform block of a frame of a video encoded with conventional residual coding, if an inferred sub-block of a transform block of an sb codeflag is not present is a DC sub-block and / or the last one of transform blocks containing a non-zero coefficient level, the decoder inferes that the sb codeflag of that sub-block is 1. And otherwise, inferring that the sb coded flag is 0. If a transform block is encoded using transform skip residual encoding, the sb coded flag of a sub-block in which no sb coded flag exists is estimated to be 1. The decoder determines an initial context value of an entropy coding model based on the sub-block flag of the inferred sub-block, and determines a sub-block flag of the encoded sub-block using the entropy coding model.

The invention relates to the field of urban road traffic pollution assessment, in particular to a city heavy diesel emission pollution field rapid description method based on dynamic point distribution, comprising the following steps: S1, constructing joint input data of road emission spatial features and meteorological conditions; s2, extracting multi-scale features of an emission space based on a residual coding structure; s3, performing adaptive modulation on the multi-scale spatial features according to meteorological conditions; s4, establishing a mapping relationship between the conditionally modulated high-dimensional spatial features and the optimal receptor stationing strategy by using a deep learning model; and the like. Compared with the prior art, on the premise that the spatial resolution of the pollution concentration field is guaranteed, the set number of pollution concentration acceptor points is remarkably reduced, and the overall efficiency of road traffic pollution emission simulation and pollution hot spot recognition is improved; an efficient and reliable technical means is provided for urban traffic environment impact assessment, pollution prevention and control decision and refined traffic management.

SUMMARY The present invention provides systems and methods for signaling a maximum transform size and residual coding methods. According to certain disclosed embodiments, the method comprises: receiving a bitstream comprising a set of pictures; determining, from the received bitstream, a value of a coding tree block size; and based on the value of the coding tree block size, determining whether to signal a flag indicating a maximum transform size of luma samples.

This invention discloses a transformer-based video decoding and filtering method, system, terminal, and storage medium. The method includes: acquiring a reference frame and a current frame; passing the reference frame and the current frame through a motion estimation network to obtain motion vectors; performing motion encoding and decoding on the motion vectors to obtain decoded motion vectors; performing motion compensation on the decoded motion vectors to obtain multi-scale context information; inputting the current frame and the multi-scale context information into a residual coding network to obtain a feature representation of the current frame; inputting the feature representation and reference features of the reference frame into a preprocessing module of a temporal context filter for preprocessing to obtain key vectors, value vectors, and query vectors constituting an attention mechanism; inputting the key vectors, value vectors, and query vectors into the filtering main module of the temporal context filter for filtering optimization; outputting a final reconstructed frame; and participating the final reconstructed frame in subsequent video decoding and filtering processes. This invention significantly improves the quality of reconstructed video.

A method for processing video data, a non-transitory computer readable medium, and an apparatus for processing video data are disclosed. The method includes determining a width (w) and a height (h) of a coding group based on a width (W) and a height (H) of a block that is non-dyadic and contains residual; and performing a conversion between a visual media data and a bitstream based on application of the coding group to the block.

Embodiments of the disclosure provide a solution for video processing. A method for video processing is proposed. The method includes: determining, for a conversion between a block of a video and a bitstream of the video, that at least one binarized bin of a syntax element (SE) for residual coding associated with the block is coded with a context, wherein the context is determined based on at least one of: coding information, a plurality of factors, a position of the SE in a residual block, a size of the residual block, at least one corresponding block of a second component, at least one neighbouring block, or a bin index; and performing the conversion based on the at least one binarized bin of the SE.

An example device includes a memory configured to store video data; and one or more processors implemented in circuitry and coupled to the memory. The one or more processors are configured to determine whether a transform skip mode is used for a current block of the video data. The one or more processors are configured to disable level mapping for residual coding based on the transform skip mode being used for the current block. The one or more processors are configured to code the current block without applying the level mapping.

A method for video processing includes determining, based on a first indication, whether a sub-block residual coding scheme is applied to residual of a current video block in a transform skip mode, the sub-block residual coding scheme splitting the residual of the current video block into multiple sub-blocks and a subset of the multiple sub-blocks have non-zero coefficients; determining, based on a second indication, a specific split pattern to be applied to the residual of the current video block, in response to the sub-block residual coding scheme being applied to the residual of the current video block; deriving, based on a third indication, the subset of the multiple sub-blocks which have non-zero coefficients; and performing a conversion on the residue of the current video block based on the determined subset of sub-blocks having non-zero coefficients.

Providing a video decoding method. [Solution] The video decoding method performed by the decoding device includes the steps of: obtaining a sign data hiding availability flag to determine whether sign data hiding is currently available for the slice; obtaining a TSRC availability flag to determine whether TSRC (Transform Skip Residual Coding) is available for the transformation skip block of the current slice; obtaining residual coding information for the transformation skip block based on the TSRC availability flag; deriving a residual sample for the transformation skip block based on the residual coding information; and generating a restored picture based on the residual sample, wherein the TSRC availability flag is obtained based on the sign data hiding availability flag.

The application discloses a kind of extremely light compression method and system, equipment, medium of electric energy metering data, the method is constructed by residual coding, zero dense transposition and zero byte segment compression three-level extremely light compression architecture, first by residual coding generation longitudinal height redundancy and the longitudinal zero dense sequence with zero byte mainly in redundant area, again by zero dense transposition, longitudinal height zero redundant area is converted into transverse continuous zero byte segment, create favorable conditions for subsequent zero byte segment compression, finally, by the compression processing of a large number of zero byte segments, while a small amount of non-zero byte is directly retained, so as to obtain compressed sequence, greatly improve the compression efficiency and decompression speed of electric energy metering data, and, the entire compression algorithm is composed of low-cost operations such as addition, subtraction, shift, comparison, etc., the MCU of electric energy meter can run without pressure, and the memory overhead is limited to a very small auxiliary table and a small amount of buffer area, which is well suited to the low-power environment of electric energy meter.

For a transform block of a frame of video encoded with regular residual coding, a decoder infers the sb coded flags of a sub-block of the transform block that is not present to be 1 if the inferred sub-block is a DC sub-block and / or the last sub-block in the transform block that contains a non-zero coefficient level. Otherwise, the sb coded flag is inferred to be 0. If the transform block is encoded with transform skip residual coding, the sb coded flag of a sub-block that is not present is inferred to be 1. The decoder determines an initial context value for the sub-block flags of an inferred sub-block based on the sub-block flags of the sub-block and uses the entropy coding model to determine the sub-block flags of the encoded sub-block.

The present application relates to a kind of for infrared image and visible light image fusion method and system, method includes: extracting shallow feature from infrared and visible light image;Obtain multiple levels of infrared and visible light features by multilevel residual coding;Obtain spatial domain and frequency domain fusion features by spatial domain fusion branch and frequency domain fusion branch;Carry out double-domain serial coupling processing, obtain spatial-frequency domain coupling fusion feature;Unified fusion guide feature is obtained by cross-layer convergence;Adaptive modulation obtains infrared and visible light high-level feature;Carry out high-level re-aggregation and reconstruction output to obtain high-level re-aggregation feature, and generate final fusion image according to high-level re-aggregation feature.Multiple levels of feature extraction simultaneously utilize spatial domain cross-modal complementary information and frequency domain amplitude-phase complementary information, through double-domain serial coupling mechanism realizes the interaction compensation and modulation of spatial information and frequency domain information, improves the target saliency of fusion image, structure definition and detail retention ability.

The present application relates to the field of urban road traffic pollution assessment, and particularly relates to a city heavy-duty vehicle emission pollution field rapid characterization method based on dynamic point distribution, comprising the following steps: S1. constructing a joint input data of road emission space characteristics and meteorological conditions; S2. extracting multi-scale characteristics of the emission space based on a residual coding structure; S3. adaptively modulating the multi-scale space characteristics according to the meteorological conditions; S4. using a deep learning model to establish a mapping relationship between the high-dimensional space characteristics after the conditional modulation and an optimal receptor point distribution strategy; and the like. Compared with the prior art, the present application significantly reduces the number of pollution concentration receptor points under the premise of ensuring the spatial resolution of the pollution concentration field, improves the overall efficiency of road traffic pollution emission simulation and pollution hotspot identification, and provides an efficient and reliable technical means for urban traffic environmental impact assessment, pollution prevention and control decision-making and fine traffic management.

The invention provides an efficient lossless compression method and system for a multi-precision floating-point feature graph, and the method comprises the steps: 1, index bit compression: employing a residual-based efficient compression method for floating-point number index bits, employing the difference of adjacent elements in the residual calculation, generating a residual signal with more concentrated statistical characteristics, and carrying out the compression of the index bits; a special residual coding mechanism is designed; step 2, mask compression: adopting a mask mechanism to mark positions of zero values and non-zero values, and compressing mask bit streams; converting the original mask into a bit sequence with a lower entropy value through an XOR operation; an improved zero value sequence coding method is adopted, and a joint compression mechanism of zero value and non-zero flag bits is introduced; and step 3, decompression. Compared with an existing optimal compression scheme, the method has the advantages that the average compression rate is increased by about 10%, and meanwhile, the total hardware area is reduced by 1.62%-16.69% compared with a current design scheme with the minimum area.

A method and apparatus for video coding. Methods and apparatuses for video coding with lossless coding mode are provided. The method includes partitioning a video picture into a plurality of CUs including a lossless CU, determining a residual coding block size of the lossless CU, and in response to determining that the residual coding block size of the lossless CU is greater than a predefined maximum value, partitioning the residual coding block into two or more residual blocks for residual coding.