64results about How to "Improve encoding performance" patented technology

The invention provides a decoding and coding method, device and equipment, and the decoding method comprises the steps: decoding a first code stream of a current image block, and obtaining a coefficient hyper-parameter feature of the current image block; for each stage sub-block of the current image block, determining a probability distribution parameter of the stage sub-block based on the coefficient hyper-parameter feature, and decoding a second code stream of the current image block based on the probability distribution parameter to obtain a residual feature of the stage sub-block; based on a mean value prediction network, determining mean value features of the sub-blocks in the stage; determining a reconstruction feature of the stage sub-block based on the mean feature of the stage sub-block and the residual feature of the stage sub-block; performing feature aggregation on the reconstruction features of the sub-blocks in each stage to obtain the reconstruction features of the current image block; a reconstructed image block of the current image block is determined based on the reconstruction feature of the current image block. Through the scheme of the invention, the coding performance and the decoding performance are improved.

The invention discloses an end-to-end video coding method based on a scale-spatial stream and hierarchical hyper-prior, and the method employs a hierarchical hyper-prior coding and decoding network to introduce hyper-prior information to assist the generation of entropy model parameters, thereby enabling an entropy model to obtain more accurate estimation probability distribution, and improving the compression efficiency. And meanwhile, the motion information of the video is better estimated in combination with a scale-spatial stream, and the video coding performance is improved by estimating a more accurate entropy model and motion information. Experimental results show that when SSIM and MS-SSIM are respectively adopted as evaluation standards, compared with an HEVC (High Efficiency Video Coding) standard, the coding method provided by the invention has the advantage that the average code rates are respectively saved by 16.40% and 15.63% under the same distortion condition for video sequences with different resolutions. Compared with a traditional video compression method, the quality of the compressed low-resolution video can be effectively improved, and a good visual effect can be obtained through the method provided by the invention.

The invention relates to a video coding method and device. The video coding method comprises the following steps: determining a luminance intra-frame reference cost, a luminance inter-frame reference cost, a chroma intra-frame reference cost and a chroma inter-frame reference cost of a current coding unit; determining a propagation cost of the current coding unit based on the luminance intra-frame reference cost, the luminance inter-frame reference cost, the chroma intra-frame reference cost and the chroma inter-frame reference cost; determining a quantization parameter offset of the current coding unit based on the luminance intra-frame reference cost, the chroma intra-frame reference cost and the propagation cost; and performing quantization processing on the current coding unit based on the quantization parameter offset, and encoding the current coding unit based on the quantization processing. According to the video coding method and device disclosed by the invention, the quantization parameter offset of the current coding unit can be determined through the propagation cost based on the luminance intra-frame reference cost, the chroma intra-frame reference cost, the chroma intra-frame reference cost and the chroma inter-frame reference cost, so that the coding performance is improved.

The invention discloses a joint optimization method for a joint photographic experts group (JPEG) quantization table and a truncation position based on rate distortion, relates to the technical field of JPEG coding optimization, and solves the technical problems that in a JPEG compression scheme, improvement of coding efficiency caused by joint optimization by using the quantization table and the truncation position is neglected, and the optimal quantization table and the optimal truncation position are difficult to find. According to the method, joint optimization is carried out on a quantization table and a truncation position of the JPEG by combining a JPEG compression method from the perspective of evolutionary computation, a strategy that the truncation position is fixed when the quantization table is optimized, a strategy that the quantization table is unchanged when the truncation position is optimized, an estimation method for designing fitness evaluation and a method based on rate-distortion optimization are respectively carried out, and the quantization table and the truncation position are optimized. The optimal quantization table and the truncation position can be effectively found, and the corresponding truncation position is optimized while multiple groups of quantization tables are generated in the optimization process; through joint optimization of the quantization table and the truncation position, image data can be compressed more effectively, redundant information is reduced, and therefore coding efficiency is improved.

The present application discloses a VVC multi-directional motion refinement optimization method based on a Merge mode from the VVC inter prediction with a Merge process with a motion vector difference, which only has a small part of coding units (CUs) to search in a large step, and fails to consider the multi-directionality of the motion in the actual process. First, the first two MV information in the extended Merge candidate list is selected as the initial MV, and is expanded from four step lengths and eight directions; it is judged whether the current step length index is greater than 1, if yes, skip the chroma block motion compensation and the bi-directional optical flow prediction mode; otherwise, skip the chroma block motion compensation, and after the optimal Merge mode is obtained, entropy coding is carried out. Compared with the VVC coding standard, the average bit rate of Y, Cb and Cr is saved by 0.57%, 0.62% and 0.25% respectively by the VVC multi-directional motion refinement optimization method based on the Merge mode.

The application provides a video coding quantization method, device, equipment and computer readable storage medium. The method comprises the following steps: obtaining a to-be-coded video frame, performing block processing and transformation processing on the to-be-coded video frame to obtain transformed video frame data; obtaining frame attribute information of the to-be-coded video frame; determining a quantization mode of the to-be-coded video frame based on the frame attribute information of the to-be-coded video frame, wherein the quantization mode is one of dependent quantization and independent quantization, wherein the dependent quantization needs to depend on the quantization result before the current to-be-quantized coefficient, and the independent quantization does not need to depend on the quantization result before the current to-be-quantized coefficient; and performing quantization processing on the transformed video frame data based on the quantization mode of the to-be-coded video frame to obtain a quantization result. Through the application, the quantization mode can be determined based on the frame attribute information of the video frame, and the quantization flexibility is improved.

The invention discloses an image coding method and system based on a region of interest, relates to the technical field of image processing, and can improve the coding effect of image coding based on the region of interest. The method is applied to an image coding system based on a region of interest, the system comprises a display, an acquisition device is arranged on the display, the method comprises the following steps: acquiring a first distance, a change angle and a focal length of eyes in a human face in real time, the first distance being a distance between the human face and the display, and the change angle being a distance between the human face and the display; the change angle is the change angle of the eye focus relative to the acquisition device; according to the first distance, the change angle, the focal length and a preset display size, determining a focusing area of the eyes in the current frame image in the display; and sending the focusing region to an encoder, so that the encoder encodes the current frame image by taking the focusing region as a region of interest.

The invention provides a decoding and coding method, device and equipment thereof. The decoding and coding method comprises the following steps: decoding a first code stream corresponding to a current image block to obtain a coefficient hyper-parameter feature; determining a probability distribution parameter based on the coefficient hyper-parameter feature, and decoding a second code stream of the current image block based on the probability distribution parameter to obtain a reconstruction feature; inputting the reconstruction features into a synthesis transformation network to obtain a reconstruction image block; the synthesis transformation network comprises an attention module, and the attention module is a cascade mixed attention module or a parallel mixed attention module; the cascaded mixed attention module comprises a first attention sub-module and a second attention sub-module, and the first attention sub-module and the second attention sub-module are serial; the parallel mixed attention module comprises a first attention sub-module and a second attention sub-module, and the first attention sub-module and the second attention sub-module are parallel. Through the scheme of the invention, the decoding performance is improved, and the complexity is reduced.

The present invention relates to a cloud computing service system using a uniform jump frame selection mode, comprising: a cloud computing server, used to use multiple encoded images before an image to be inter-frame encoded as multiple frames to be selected for the inter-frame encoded image, the number of the multiple encoded images being equal to a targeted search number; and a coding processing device, used to select a frame to be selected that has a signal-to-noise ratio closest to the signal-to-noise ratio of the image to be inter-frame encoded as a reference frame for performing inter-frame encoding on the image to be inter-frame encoded. Through the present invention, in an inter-frame encoding mechanism based on cloud computing, the search number of reference frames selected for inter-frame encoding can be determined based on the horizontal resolution of the video content of the image to be inter-frame encoded and the vertical resolution of the video content, and the multiple encoded images corresponding to the search number before the image to be inter-frame encoded are used as multiple frames to be selected for the inter-frame encoded image by using a uniform jump frame selection method, thereby improving the encoding effect of the inter-frame encoding processing.

The invention provides a composite fluorescence coding method for a biomarker and application of the composite fluorescence coding method. A composite fluorescent coding method for a biomarker comprises the following steps: a composite structure formed by connecting tetrahedral DNA frames with the same side length in series is used as a coding carrier, one of the tetrahedral DNA frames is used for loading fluorescent coding dyes with different colors to realize the distinguishing of different biological targets, and the other tetrahedral DNA frame is used for loading fluorescent coding dyes with different colors; the other tetrahedral DNA framework is used for loading quantitative dye and a recognition probe, so that quantitative analysis of the biological target is realized. Single chains respectively extend out of the same sides of the tetrahedral DNA framework, and are connected in series and assembled according to a base complementary pairing principle to obtain the coding vector. According to the invention, a composite structure formed by series connection of TDF is used as the coding vector, so that the problems of biotoxicity, easy degradation by nuclease and the like of a traditional inorganic material and a two-dimensional DNA nano-material are solved, and long-term structural stability of the coding vector in living cells is realized.

The invention provides a decoding and coding method, device and equipment thereof. The decoding and coding method comprises the following steps: decoding a first code stream corresponding to a current image block to obtain a coefficient hyper-parameter feature; determining a probability distribution parameter based on the coefficient hyper-parameter feature, and decoding a second code stream of the current image block based on the probability distribution parameter to obtain a reconstruction feature; inputting the reconstruction features into a synthesis transformation network to obtain a reconstruction image block; the synthesis transformation network comprises an attention module, and the attention module is a cascade mixed attention module or a parallel mixed attention module; the cascaded mixed attention module comprises a first attention sub-module and a second attention sub-module, and the first attention sub-module and the second attention sub-module are serial; the parallel mixed attention module comprises a first attention sub-module and a second attention sub-module, and the first attention sub-module and the second attention sub-module are parallel. Through the scheme of the invention, the decoding performance is improved, and the complexity is reduced.

This application provides a decoding and encoding method, apparatus, and device. The method includes: obtaining a target probability distribution model corresponding to a first scaling factor based on a first bitstream corresponding to a current block; decoding a second bitstream corresponding to the current block based on the target probability distribution model corresponding to the first scaling factor to obtain corrected residual features corresponding to the current block; and determining a reconstructed image block corresponding to the current block based on the corrected residual features. This application improves encoding and decoding performance.

The embodiment of the present application discloses an inter-frame prediction method, an encoder, a decoder and a computer storage medium. The decoder parses a code stream to obtain a prediction mode parameter of a current block; when the prediction mode parameter indicates that an inter-frame prediction value of the current block is determined using the inter-frame prediction mode, a first motion vector of a sub-block of the current block is determined; wherein the current block includes multiple sub-blocks; based on the first motion vector, a first prediction value of the sub-block and a first motion vector deviation between each pixel position in the sub-block and the sub-block are determined; according to the first motion vector deviation, a center position and a second motion vector deviation corresponding to each pixel position are determined; based on the first prediction value, secondary prediction or PROF processing is performed according to the center position and the second motion vector deviation to determine a second prediction value of the sub-block, and the second prediction value is determined as the inter-frame prediction value of the sub-block.

The present invention provides a method and system for training an image coding and decoding model based on deviation control, which belongs to the field of image coding and decoding. The method comprises: determining a total loss function based on a deviation control loss function and a rate-distortion loss function, training the image coding and decoding model based on the total loss function, and obtaining a trained image coding and decoding model; the calculation formula of the deviation control loss function is:; by performing deviation control on a feature map and a Gaussian mean, the difference between the feature map and the estimated Gaussian mean value is reduced, so that the elements to be encoded are smaller, the feature map is closer to the peak value of the predicted Gaussian distribution, the variance of the Gaussian distribution is reduced, and the speed and encoding performance of entropy coding and decoding are improved.

Embodiments of the present application provide a video processing method, device, computer equipment, storage medium and program product. The video processing method comprises: obtaining a target video frame to be encoded from a target video; obtaining a video attribute feature of the target video, determining an encoding offset parameter matched with the video attribute feature; performing quantization parameter estimation on the target video frame according to the encoding offset parameter, obtaining an initial quantization parameter of the target video frame; adjusting the initial quantization parameter of the target video frame to obtain an encoding quantization parameter of the target video frame; and performing encoding processing on the target video frame according to the encoding quantization parameter of the target video frame. According to the embodiments of the present application, the encoding quantization parameter can be determined for video encoding.

The invention provides a decoding and coding method, device and equipment, and the decoding method comprises the steps: obtaining a first feature corresponding to a current image block through a first neural network, and obtaining a feature adjustment factor corresponding to the current image block, the first neural network comprising at least one convolution layer; determining a target feature based on the first feature and the feature adjustment factor; and obtaining a reconstructed image block corresponding to the current image block through a second neural network based on the target feature, the second neural network comprising at least one convolutional layer. Through the technical scheme of the invention, the coding performance and the decoding performance can be improved.

The invention provides a video coding parameter processing method, a video coding method and related equipment, and relates to the technical field of video processing. The method comprises the following steps: acquiring a preset encoding frame rate and at least one encoder supported by a client; based on a preset coding frame rate, carrying out coding performance detection on the at least one coder to obtain a detection result corresponding to the preset coding frame rate; if the detection result corresponding to the preset coding frame rate is passing, determining that the preset coding frame rate is a target coding frame rate; and obtaining at least one selectable encoder corresponding to the target coding frame rate, performing coding configuration evaluation on the at least one selectable encoder, and obtaining a target encoder and target coding configuration information of the target encoder. According to the method, the performance of the client encoder is dynamically detected, and the optimal encoding frame rate, the optimal encoder and the optimal configuration are selected according to the detection result, so that the encoding suitability is improved, and a better encoding effect can be achieved in different client environments.

The application provides a decoding and encoding method, device and equipment, including: decoding a first code stream corresponding to a current image block to obtain a coefficient hyperparameter feature; determining a probability distribution parameter based on the coefficient hyperparameter feature, and decoding a second code stream of the current image block based on the probability distribution parameter to obtain a reconstructed feature; inputting the reconstructed feature into a synthesis transformation network to obtain a reconstructed image block; the synthesis transformation network includes an attention module, and the attention module is a cascaded hybrid attention module or a parallel hybrid attention module; the cascaded hybrid attention module includes a first attention submodule and a second attention submodule, and the first attention submodule and the second attention submodule are in series; the parallel hybrid attention module includes a first attention submodule and a second attention submodule, and the first attention submodule and the second attention submodule are in parallel. The application improves the decoding performance and reduces the complexity.

The present invention provides a dual-protograph LDPC code encoding optimization method, device and product for underwater acoustic communication, the method comprising: setting the initial dimension of the protograph matrix to m rows and n columns for a source or a channel; setting the target number of connections of the total number of connections existing in the m×n nodes of the protograph matrix; randomly assigning values ​​so that the total number of connections is equal to, thereby determining the connection relationship of the nodes in the protograph; constraining the degree values ​​of the nodes according to the connection relationship of the nodes in the protograph matrix, and obtaining a first adjacent protograph matrix; optimizing the degree values ​​in the first adjacent protograph matrix using a differential evolution algorithm and a predetermined degree value optimization target, and obtaining an optimized second adjacent protograph matrix. The technical solution of the present invention uses the connection relationship to constrain the degree values ​​of the nodes, optimizes the degree distribution and connection structure of the protograph matrix, and reduces the complexity of the optimization design of the LDPC code protograph matrix.

The invention provides a training method and device for an image coding large model of a pathological section, and belongs to the technical field of computer vision and deep learning. The method comprises the following steps: constructing a pathological section image training set and a verification set; constructing an image coding large model for the pathological section, wherein the image coding large model is composed of a pre-training model and an additionally-added task head; freezing the pre-training model, training a task head by using the training set, and checking by using the verification set to obtain a task head after preliminary training; and unfreezing the pre-training model, performing fine tuning training on the large model by using the training set, and performing inspection by using the verification set to obtain a finally trained large model. According to the method, the task head and the pre-training model are trained in stages, so that interference of initial training on the pre-training model can be effectively avoided, finally, in a pathological section image coding task, the performance of an actual task is improved, and then the coding effect and adaptability of the model on the pathological section image are improved.

The invention discloses a depth image coding method and device for saliency segmentation, electronic equipment, a medium and a product, and relates to the technical field of image coding, and the method comprises the steps: obtaining the saliency value of each pixel point in a target image, and determining the saliency probability distribution of the target image according to the saliency value of each pixel point; calculating a weight distribution value of each pixel point based on a preset activation function and the significance probability distribution; performing channel cutting on the original potential features of the target image according to the weight distribution values to obtain coding potential features, and coding the coding potential features based on a preset coding network to obtain a coding result, the weight distribution value is related to the distribution proportion of the corresponding pixel point in the first storage bit stream, and the larger the weight distribution value is, the higher the corresponding distribution proportion in the first storage bit stream is. According to the invention, the technical problem of low performance of depth coding in a downstream saliency detection task is solved.

The invention provides a decoding and coding method, device and equipment, and the decoding method comprises the steps: obtaining a first feature corresponding to a current image block through a first neural network, and obtaining a feature adjustment factor corresponding to the current image block, the first neural network comprising at least one convolution layer; determining a target feature based on the first feature and the feature adjustment factor; and obtaining a reconstructed image block corresponding to the current image block through a second neural network based on the target feature, the second neural network comprising at least one convolutional layer. Through the technical scheme of the invention, the coding performance and the decoding performance can be improved.

The present disclosure relates to an encoding method, a decoding method, a device, an electronic device and a readable storage medium. The encoding method comprises: obtaining a first coefficient sequence of a to-be-encoded CG block, wherein the first coefficient sequence comprises a first absolute value and a first sign value of each coefficient in the to-be-encoded CG block; determining a first index of the first coefficient sequence and a first sign value of a first N non-zero coefficients, wherein the first index is a value obtained by performing a preset processing on each first absolute value, and N is an integer greater than 1; determining a second absolute value and a second sign value of each coefficient in the first coefficient sequence based on a comparison between the first index and the first sign value of the first N non-zero coefficients and a preset sign index table, to obtain a second coefficient sequence; and encoding the second coefficient sequence to obtain encoding information of the to-be-encoded CG block, wherein the second sign value of the first N non-zero coefficients in the second coefficient sequence is not encoded. The method can improve the encoding performance.

A video decoding method performed by a decoding apparatus according to the present document may comprise the steps of: obtaining, from a bitstream, information indicating a level value of a transform coefficient in a current block; selecting one Rice parameter look-up table for the information indicating the level value of the transform coefficient, from among a plurality of Rice parameter look-up tables; deriving a Rice parameter for the information indicating the level value of the transform coefficient on the basis of the selected Rice parameter look-up table; deriving a bin string for the information indicating the level value of the transform coefficient on the basis of the Rice parameter; and deriving the level value of the transform coefficient on the basis of the bin string.

This application provides a video transcoding method, system, electronic device, and storage medium, belonging to the field of video processing technology. The method includes: acquiring a video stream; decapsulating the video stream to obtain decapsulated data; extracting dynamic metadata from the video stream; traversing the dynamic metadata to determine if a scene change exists; when traversing the dynamic metadata determines that a scene change exists, recording the target dynamic metadata corresponding to the scene change; determining the target frame number based on the target dynamic metadata; determining the scene-changing frame and non-scene-changing frames in the video stream based on the target frame number; adjusting the encoding parameters of the scene-changing frames and / or non-scene-changing frames during re-encoding; and performing video encoding processing based on the adjusted encoding parameters to obtain a transcoded bitstream. In this way, dynamic metadata is used to identify video scene changes, and re-encoding is performed based on scene changes to adjust the bitrate. Non-scene-changing frames reduce the number of code bytes, saving total codewords and improving encoding performance.

Embodiments of the present application provide a data processing method and apparatus, an electronic device, and a storage medium. The method comprises: determining a prediction table corresponding to attribute information of a point cloud (110); determining a residual and a predicted value index of the attribute information according to the prediction table (120); and encoding the residual and the predicted value index to form a code stream for sending or storing (130).

The invention relates to the technical field of image coding, and provides an image coding method and device, terminal equipment and a decoding method, and the coding method comprises the steps: obtaining a to-be-coded image block; processing the to-be-coded image block according to a preset rule to obtain a target to-be-coded image block; the processing comprises single channel tree division; and coding the target to-be-coded image block to obtain a target coding result. According to the image coding method, the image coding efficiency can be improved.

A video decoding method performed by a decoding apparatus according to the present document may comprise the steps of: obtaining, from a bitstream, information indicating a level value of a transform coefficient in a current block; selecting one Rice parameter look-up table for the information indicating the level value of the transform coefficient, from among a plurality of Rice parameter look-up tables; deriving a Rice parameter for the information indicating the level value of the transform coefficient on the basis of the selected Rice parameter look-up table; deriving a bin string for the information indicating the level value of the transform coefficient on the basis of the Rice parameter; and deriving the level value of the transform coefficient on the basis of the bin string.

The invention provides a crew personalized ship recommendation method based on a graph neural network and Transform enabling, and the method comprises the steps: constructing a knowledge graph of multiple entity types, and converting dispersed maritime data into a structured semantic relation network; the method comprises the following steps: acquiring maritime data by adopting a multi-source data fusion strategy, and preprocessing the maritime data to obtain a triple data set; a variational heterogeneous graph auto-encoder is designed, and unified representation and potential association modeling of multi-source heterogeneous data are achieved; constructing a breadth-depth dual-channel knowledge graph aggregation model which comprises a breadth channel, a depth channel and a dual-channel self-attention fusion module; a user-relation-entity three-dimensional joint contrast learning framework is designed, a user-relation-entity is taken as a core dimension, and a semantic boundary is enhanced in an embedding space by constructing a multi-type sample pair and a joint loss function, so that entity representation distances with similar semantics are shortened, entity representation distances with irrelevant semantics are deduced, and a user-relation-entity three-dimensional joint contrast learning framework is obtained. And finally, outputting an accurate ship recommendation result.