195 results about "Residual coding" patented technology

The invention discloses a high-resolution solar radiation data correction method and system based on deep learning, and the method comprises the steps: obtaining meteorological data and digital elevation model data, and carrying out the preprocessing; dynamically optimizing parameter configuration of the WRF model, and simulating and outputting high-temporal-spatial-resolution meteorological data as training data; fusing solar radiation flux values in meteorological reanalysis data and near-real-time product meteorological data as label data of a correction model; inputting the high-temporal-spatial-resolution meteorological data and the label data into a pre-constructed multi-scale feature fused deep residual coding and decoding network model for training, and obtaining an optimal parameter model based on multiple loop iterations; and correcting solar radiation flux data output by the WRF mode by using the optimal parameter model. According to the method, the problem that the radiation variable value output by the WRF in the traditional numerical weather mode is consistent with the real data trend but deviates is effectively solved, and the reliability of meteorological data simulation is enhanced.

The invention relates to the technical field of data compression and storage, and discloses a monitoring data compression and storage method driven by a time sequence database, comprising the following steps: S1, preprocessing multi-source monitoring data, and constructing a dynamic tensor comprising 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 a compression parameter, a decompression parallelism degree and an 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 lightweight residual coding result. Through a 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 fact that the streaming monitoring data cannot adapt to dynamic newly-added tags are solved, and meanwhile, frequent reconstruction cost caused by data dynamic expansion is avoided.

Aspects of the disclosure provide methods and apparatuses for video data processing. In some examples, an apparatus for video data processing includes processing circuitry. For example, the processing circuitry determines a first syntax element for coding control in a first scope of coded video data in a bitstream. The first syntax element is associated with a coding tool of a slice based Rice coding for a residual coding in a transform skip mode. The coding tool provides a Rice parameter at a slice level for the residual coding in the transform skip mode. In response to the first syntax element being a first value indicative of disabling of the coding tool in the first scope, the processing circuitry decodes the first scope of coded video data that includes one or more second scopes of coded video data without invoking the coding tool.

The invention discloses a training method, a segmentation method and a device of a multi-mode weak supervision medical image segmentation model. The method comprises the following steps: unifying the size of a medical image; in the first stage of the network model, CAM graphs under different scales are extracted through a residual coding network, and single-mode CAM graphs under different scales are merged through a Sigmoid activation function; fusing CAMs of different modes; encoding a foreground image, a background image, a text label corresponding to the foreground image and a text label corresponding to the background image by using CLIP, calculating the similarity between an image encoding vector and a corresponding text encoding vector, and maximizing the similarity as a loss item; meanwhile, taking an opposite number of an absolute value of a difference value between the CAM of the foreground image and the CAM of the background image as one of loss items to train a model; performing foreground and background segmentation on the final CAM by taking 0.5 as a threshold value, and calculating a final Dice score with a real label so as to evaluate the performance of the model; according to the method, the multi-modal CAM fusion problem can be solved by utilizing the strong representation capability of the large model.

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 and device for decoding an encoded data propose to determine a residual error image based on the decoded image only and generated by an invertible neural network without needed any additional signaling data. The residual error image is combined with the decoded image, resulting into an enhanced image. The invertible neural network is trained to determine, in forward pass, a latent variable from a decoded image and a residual coding map and to determine, in backward pass, a reconstructed residual map from a decoded image and a random residual map, so that the latent variable follows a normal distribution or a uniform distribution.

The invention discloses an electric energy meter data compression method and system, electronic equipment and a storage medium, and the method comprises the steps: carrying out the first-order differential processing of an electric quantity measurement data sequence, obtaining a residual data sequence, greatly reducing the value domain of the residual data sequence, greatly improving the repetition, and remarkably reducing the statistical entropy; low-entropy and high-redundancy ideal input is created for subsequent coding, and the compression ratio is integrally improved. According to the method, the residual data sequence is subjected to coding processing, positive and negative information is reserved, the problem that complement storage equivalent entropy is not reduced is avoided, bit column recombination processing or byte column recombination processing is performed on the residual coding sequence, and a large number of continuous data streams of local repeated fragments are generated, so that in an electric energy meter environment in which the MCU computing power and the RAM are limited subsequently, the residual data sequence is subjected to bit column recombination processing or byte column recombination processing. The lightweight compression algorithm can also quickly discover and reuse redundancy in an extremely short window, and the overall compression efficiency is remarkably improved.

The invention relates to an end-to-end optimized prediction video coding method and device, and belongs to the field of video coding. According to the method, a B frame coding model performs motion estimation on a to-be-coded frame by respectively utilizing information of a forward reference frame and a backward reference frame, so that motion information and content change in a video sequence can be more accurately captured, more accurate characteristics and prior information are provided for residual coding, and the coding performance of the model is further improved. Through the bidirectional information acquisition and processing mode, the comprehensive understanding of the time-space characteristics of the video sequence is improved, and the processing of the model on the motion and content change in the coding process is effectively optimized, so that the more excellent video compression performance is realized.

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.

The invention discloses a two-stage pulse data lossless coding method and device based on lossy coding and residual coding. Through a deep neural network, the preprocessed pulse data are used as input, probability distribution of latent variables and residual errors is obtained through two stages of lossy coding and residual error coding, and therefore corresponding code stream files are output, and the purpose of lossless compression of the pulse data is achieved. The existing coding model is not suitable for processing pulse data or is difficult to realize lossless coding; according to the method, a first pulse data lossless coding model is adopted, a bit splicing data preprocessing mode is adopted, so that the neural network is easier to mine data correlation, and a two-stage framework of lossy coding and residual coding is applied to ensure lossless coding. On the basis of the mode, the neural network coding model can be integrally optimized by utilizing an end-to-end training method, so that better pulse data lossless coding performance is obtained.

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.

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

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.

Methods, apparatuses, and non-transitory computer-readable storage mediums are provided for video coding with a low-delay transform skip residual coding (TSRC) method. The TSRC method includes: deriving, by an encoder, a rice parameter based on coded information of a current slice of a video. The coded information may include one or more of following parameters: a quantization parameter or a coding bit-depth associated with a slice, a picture, or a sequence of the video; or a hash ratio associated with the slice, the picture, or the sequence of the video.

The present invention discloses a 3D biomedical video compression method, system, device and storage medium. Through a 3D biomedical video compression framework including 3D motion estimation, motion vector coding, 3D motion compensation and residual coding, the 3D biomedical video compression performance can be greatly improved and important information in the 3D biomedical video can be retained.

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 discloses a breast lesion image semi-supervised segmentation method. The method belongs to the technical field of medical image processing and semi-supervised learning. The technical problem of improving the feature extraction capability of a semi-supervised segmentation network in a complex breast lesion segmentation scene under a small number of labeled samples and realizing accurate segmentation of a breast lesion is solved. A dual-scale image of a mammary gland image is generated, so that the network can learn features of mammary gland lesions from different scales, the ability of the network to extract features of mammary gland lesions with large size and form differences is improved, data perturbation is performed on the dual-scale image, and a generator performs mutual generation on segmentation confidence maps of a source image and a perturbation image. And the network stability is improved. Through cascade inverse residual coding feature fusion and decoding feature fusion, more potential features are mined by using existing features, the segmentation performance of the network is improved under a small number of labeled samples, and accurate segmentation of a breast lesion can be realized by inputting a breast image into a final segmentation network.

An image encoding / decoding method and apparatus are provided. An image decoding method according to the present disclosure may comprise obtaining a reconstructed picture, determining a target boundary of deblocking filtering in the reconstructed picture, determining a boundary strength for the target boundary, and applying deblocking filtering to the target boundary based on the boundary strength. Based on the target boundary being a transform block boundary and a color component of the reconstructed picture being a chroma component, the boundary strength may be determined based on whether joint CbCr residual coding is performed on at least one of two blocks adjacent to the target boundary, and the joint CbCr residual coding may correspond to encoding residual samples for a chroma Cb component and a chroma Cr component as a single transform block.

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.

The invention discloses an aircraft rotating frame detection method and system based on cyclic angle coding, and relates to the technical field of image processing, and the method comprises the steps: obtaining a target image of a to-be-detected aircraft; performing cyclic angle coding on the angle domain to obtain a cyclic angle coded value; performing angle prediction on the target image based on the cyclic angle coded value to obtain an angle initial coded value and an angle residual coded value of the to-be-detected aircraft; generating a target angle coded value of the to-be-detected aircraft according to the angle initial coded value and the angle residual coded value; decoding the target angle coded value into a target angle value; and carrying out rotation constraint on the sampling frame based on the target angle value to obtain a target frame, and carrying out feature extraction on the target image based on the target frame. According to the invention, the coding space and the physical angle space are strictly isomorphic in the topological structure, and the problem of boundary fracture is avoided; and the feature space alignment precision during rotation of the aircraft can be improved, so that the rotating frame of the aircraft can be detected more accurately.

The present disclosure provides systems and methods for performing residual encoding of video data. According to certain disclosed embodiments, the method comprises: receiving control information for encoding a video sequence; and determining an encoding method for encoding a prediction residual signal of an encoding block in the video sequence based on the control information. The coding method is one of transform residual coding and transform skip residual coding.

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 discloses an air conditioner fault early warning system and method based on deep learning, and the method comprises the following steps: S1, collecting data, forming current multi-channel time sequence input data, and obtaining a historical fault-free operation data sample; s2, constructing a normal state prototype sample; s3, generating prototype residual error coding features; s4, inputting the current multi-channel time sequence input data and the prototype residual encoding features into the improved multi-scale convolution branch network to obtain original feature branches and residual feature branches, and introducing a causal-guided convolution kernel selection mechanism; s5, fusing the original feature branch and the residual feature branch; s6, obtaining an abnormal score value based on fusion feature representation; s7, the abnormal score value is compared with a preset threshold value, and an air conditioner fault early warning instruction is output; and S8, when the abnormal score value does not reach the preset threshold value, updating the prototype sample in the normal state. The air conditioner fault early warning method improves the accuracy and self-adaptive capacity of air conditioner fault early warning, and is suitable for intelligent operation and maintenance scenes of an air conditioner system.

The present disclosure provides systems and methods for performing residual encoding of video data. According to certain disclosed embodiments, the method comprises: receiving control information for encoding a video sequence; and determining an encoding method for encoding a prediction residual signal of an encoding block in the video sequence based on the control information. The coding method is one of transform residual coding and transform skip residual coding.

The present disclosure provides systems and methods for performing residual coding of video data. According to certain disclosed embodiments, the methods include: receiving control information for coding a video sequence; and determining, based on the control information, a coding method for coding a prediction residual signal of a coding block in the video sequence. The coding method is one of a transform residual coding and a transform-skip residual coding.

To provide an image decoding method performed by a decoding device.SOLUTION: The method includes the steps of: acquiring prediction-related information for a current block; acquiring a dependent quantification enable flag related to whether dependent quantification is available; acquiring, on the basis of the dependent quantization enable flag, a transform skip residual coding (TSRC) enable flag related to whether TSRC is available; acquiring residual information of residual coding syntax for the current block, which has been derived on the basis of the TSRC enable flag; deriving motion information of the current block on the basis of the prediction-related information; deriving a prediction sample of the current block on the basis of the motion information; deriving a residual sample of the current block on the basis of the residual information; and generating a reconstructed picture on the basis of the prediction sample and the residual sample.SELECTED DRAWING: Figure 13

Provided are a method and apparatus for encoding / decoding an image. A method for decoding an image according to the present disclosure may comprise the steps of: obtaining a reconstructed image; determining a target boundary of deblocking filtering in the reconstructed image; determining the boundary strength of the target boundary; and applying deblocking filtering to the target boundary based on the boundary strength, in which when the target boundary is a transform block boundary and a color component of the reconstructed image is a chroma component, the boundary strength may be determined based on whether joint CbCr residual coding is performed on at least one of two blocks adjacent to the target boundary, and when the target boundary is a transform block boundary and the color component of the reconstructed image is a chroma component, the boundary strength may be determined based on whether joint CbCr residual coding is performed on at least one of the two blocks adjacent to the target boundary. And the joint CbCr residual encoding may correspond to encoding residual samples of the chroma Cb component and the chroma Cr component into a single transform block.