130 results about "Rate distortion" patented technology

The invention discloses a video compression intelligent preprocessing method, system and device based on frequency domain perception optimization and a medium. The method comprises the following steps: constructing a preprocessing model; preprocessing the input coding frame and the reference frame; enabling the preprocessed coding frame and reference frame to pass through a virtual encoder to obtain a frequency domain coefficient of a residual frame, and calculating a code rate of the coding frame; enabling the frequency domain coefficient of the residual frame to pass through a virtual decoder to obtain a decoded frame; training a preprocessing model; testing the effect; the system, the equipment and the medium are used for implementing the method. According to the method, a frequency domain sensing module is introduced into a virtual encoder in a training stage, modeling is carried out on a frequency domain information context, and statistical redundancy between transformation units is eliminated; an optical flow collaboration module is introduced into a virtual encoder, local distortion of a prediction frame is repaired in a feature domain by using high-level semantic information, and the difference between training and actual deployment is effectively reduced; through the optimization, the preprocessing model can better learn the rate distortion characteristic of the standard encoder, and the quality of the preprocessed video is remarkably improved.

The invention provides a communication segmentation learning system and method for adaptive channel compression, and a medium, and relates to the technical field of segmentation learning and communication compression. The system comprises a plurality of clients, a server side and a channel compression device arranged between the clients and the server side, the channel compression device comprises a channel sensitivity modeling module, a rate distortion adaptive compression module and a cross-client fair coordination module. In a channel sensitivity modeling module, channel importance is dynamically evaluated through intermediate layer activation value fusion; differentiated quantization and compression strategies are designed on the basis of sensitivity scores in a rate-distortion self-adaptive compression module, so that key information is reserved while communication overhead is reduced; and meanwhile, the cross-client fair coordination module realizes balanced distribution of communication resources among multiple clients through a fairness regularization and dual optimization mechanism, so that the influence of excessive compression on global convergence is avoided. According to the method, the communication efficiency and the training stability of segmentation learning in a complex heterogeneous environment are remarkably improved.

The embodiment of the invention provides a Gaussian point cloud rendering method and device, equipment and a storage medium, and relates to the technical field of computer vision. The method comprises the following steps: acquiring pixel points of foreground targets in two corresponding key frames, generating a double-view-angle Gaussian point cloud based on the pixel points, quantifying double-view-angle Gaussian parameters of the double-view-angle Gaussian point cloud based on different rate-distortion coefficients to obtain quantized Gaussian parameters corresponding to each rate-distortion coefficient, and obtaining the target foreground target in the two key frames according to the quantized Gaussian parameters of the double-view-angle Gaussian point cloud and the quantized Gaussian parameters of the double-view-angle Gaussian point cloud. At least entropy coding is carried out on the quantized Gaussian parameter to obtain a coded Gaussian parameter; and determining a target rate-distortion coefficient according to the definition requirement, selecting a coding Gaussian parameter corresponding to the target rate-distortion coefficient as a target coding Gaussian parameter, and sending at least one target coding Gaussian parameter corresponding to each dual-view sequence to a decoding end. The frame extraction operation is performed on the video frame, so that the data volume can be reduced. Secondly, quantitative Gaussian parameters corresponding to different definitions are obtained according to different rate distortion coefficients, and balance of data transmission and rendering quality is achieved.

Given a sequence of images in a first codeword representation, methods, processes, and systems are presented for image reshaping using rate distortion optimization, wherein reshaping allows the images to be coded in a second codeword representation which allows more efficient compression than using the first codeword representation. Syntax methods for signaling reshaping parameters are also presented.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, for a conversion between the current video block and a bitstream of the video, a target number for a set of motion candidates, the target number being smaller than or equal to an upper limit value; determining, based on the target number and a fast rate distortion optimization (RDO) process, the set of motion candidates from a plurality of motion candidates for an intra block copy (IBC) based mode for coding the current video block; and performing the conversion based on the set of motion candidates.

The present disclosure relates to picture encoding and decoding of image regions on tile-basis. In particular, multiple components of an input tensor including a first and second component in spatial dimensions is processed within multiple pipelines. The processing of the first component includes dividing the first component in the spatial dimensions into a first plurality of tiles. Likewise, the processing of the second component includes dividing the second component in the spatial dimensions into a second plurality of tiles. The respective first and second plurality of tiles are then processed each separately. Among the first and second plurality of tiles there are at least two respective collocated tiles differing in size. In case of compression, the processing of the first and / or second component includes picture encoding, rate distortion optimization quantization, and picture filtering. In case of decompression, the processing includes picture decoding and picture filtering.

Methods, apparatus, systems, and articles of manufacture are disclosed to improve video encoding. An example apparatus includes at least one memory, instructions, and processor circuitry to generate a pool of clipping index set candidates by executing a machine learning model, select a clipping index set from the pool of the clipping index set candidates based on a rate distortion cost associated with the clipping index set, the clipping index set including clipping coefficients, and filter a video frame based on the clipping coefficients.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, for a conversion between a video unit of a video and a bitstream of the video unit, whether to apply at least one neural network (NN) filter model or determine a rate distortion cost during a rate distortion optimization (RDO) process of the video unit based on at least one of: a distortion without NN filter model, a distortion with n-th NN filter model, a combination of distortions of a plurality of NN filter models, or coding statistics of the video unit, and wherein n is an integer number; determining a coding mode of the video unit based on a rate distortion optimization (RDO) criterion in the RDO process; and performing the conversion based on the coding mode.

The embodiment of the invention provides an end-to-end image compression method and system based on window local attention and generalized chessboard space channel context, and belongs to the technical field of image processing. The method comprises the following steps: constructing a transformation network based on an attention module and a stacked residual block; the transformation network based on the attention module and the stacked residual block is used for executing adaptive transformation of contents through dynamic representation and neighborhood information embedding to obtain potential features; establishing a generalized chessboard space channel context model; the generalized chessboard space channel context model is used for carrying out entropy coding on the potential features; and obtaining image compression data according to the transformation network based on the attention module and the stacked residual block and the generalized chessboard space channel context model. According to the method, redundancy can be eliminated to the maximum extent, excellent rate distortion performance is achieved, and meanwhile high-throughput parallel computing efficiency is ensured.

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 invention discloses a video coding method based on multi-domain perception feature fusion, and belongs to the technical field of image communication. The method comprises the following steps: extracting perception features of a space domain, a time domain and a frequency domain from an input video frame sequence; normalizing the multi-domain sensing features, and generating a sensing importance factor for each coding unit through a dynamic fusion weight mechanism; constructing perceptual distortion evaluation based on perceptual importance factors, replacing a traditional rate distortion objective function, and guiding code rate distribution of coding units; and according to the perception importance factor, performing nonlinear mapping by using a hyperbolic tangent function, calculating to obtain a coding unit level quantization parameter adjustment amount, and obtaining a final quantization parameter in combination with the basic quantization parameter, thereby realizing adaptive rate distortion optimization. According to the method, the visual sensitive area can be accurately identified, and the code rate is remarkably reduced while the subjective visual quality is guaranteed.

The invention provides a video coding method and device, electronic equipment, a storage medium, a program product and a bit stream generation method, and the video coding method comprises the steps: traversing a plurality of preset coding modes for a current block, and obtaining the rate distortion cost in each preset coding mode; selecting a coding mode of the current block from a plurality of preset coding modes based on the rate distortion cost in each preset coding mode; encoding the current block based on the encoding mode of the current block; wherein the step of acquiring the rate distortion cost in each preset coding mode comprises the following steps: acquiring a subjective quality index corresponding to the current coding mode; a penalty coefficient associated with the subjective quality index is calculated, and the penalty coefficient is in positive correlation with the possibility of the subjective quality problem indicated by the subjective quality index; and based on the penalty coefficient, amplifying the original rate-distortion cost of the current coding mode to obtain the rate-distortion cost of the current coding mode. The method can improve the subjective quality of the coded video.

The invention discloses a VVC code rate control algorithm based on deep reinforcement learning, and the algorithm comprises the following steps: importing a video sequence into an encoder, and enabling the video sequence to enter initial frame coding; after the encoder completes the default encoding of the first two frames, the subsequent frame prediction firstly extracts the encoding state information of the previous prediction frame, and a greedy strategy is adopted to perform action selection; an overall reward value is obtained through CTU-level code rate control and an actual coding process in sequence; observing the next state and the last reward, performing TD iteration on the Q value, and adding the Q value into the Q value network after TD iteration; setting an experience playback pool; after the capacity of the experience playback pool reaches a threshold value, randomly sampling from the experience playback pool in batches; resetting the Q value network; and carrying out coding test based on the Q value network obtained by training. The VVC code rate control algorithm based on deep reinforcement learning has a good capability of guiding code rate control coding, and compared with standard code rate control in VTM13.0, the VVC code rate control algorithm based on deep reinforcement learning can bring high rate distortion performance and improve code control precision.

The invention relates to a three-dimensional point cloud prediction geometric coding method based on deep learning, and the method comprises the steps: 1, forming a prediction tree through points collected by each laser transmitter, and converting an original laser radar point cloud LPC into a plurality of prediction trees for representation; 2, respectively designing different predictors and entropy encoders for each component of the coordinates of the points, and compressing each component of the coordinates of the points by applying different quantization step lengths; 3, selecting a quantization step size for quantifying each component by adopting a quantization step size selection strategy; 4, adopting an entropy model to model the probability distribution of the residual error of each component so as to encode the residual error entropy; and step 5, decoding is realized through a reverse process from the step 1 to the step 4. Compared with other methods, the method provided by the invention obtains the best rate distortion performance.

The invention discloses a video coding method based on conditional probability and reconstruction distortion propagation optimization, which comprises the following steps of: constructing a prospective image set, deciding a coding structure, constructing a block-level time domain reference relation chain, calculating accumulated distortion offset and determining time domain quantization parameter offset, calculating the prediction cost of each image block corresponding to each frame of image in the look-ahead image set based on the reference frame list, determining a reference block according to the prediction cost so as to construct a block-level time domain reference relation chain, and constructing a distortion dependency item based on the block-level time domain reference relation chain, and calculating an accumulated distortion offset based on the distortion dependency so as to calculate a time domain quantization parameter offset of each image block, and coding the to-be-coded reference frame based on the time domain quantization parameter offset. A reference frame list consistent with an actual coding process is set, so that a distortion propagation path of time domain distortion on a reference relation chain in the actual coding process is simulated, an expression of a distortion dependency item is reconstructed, and the rate distortion performance is improved.

The invention provides a video coding method, which comprises the following steps of: inputting a coding tree unit to be coded, and extracting texture features of a coding block, the texture features comprising local binary pattern similarity of all pixel points in the coding block and direction dispersion of each pixel point; inputting the texture features into the trained multi-type division prediction architecture, and sequentially judging whether to execute quadtree division, horizontal or vertical division, horizontal binary tree or ternary tree division and vertical binary tree or ternary tree division or not through a binary classification problem method; and calculating the rate distortion cost under each division mode to obtain an optimal division mode and a suboptimal division mode of the coding block, and outputting an optimal mode or a combination of the optimal mode and the suboptimal mode. According to the invention, the accuracy of the prediction mode in coding is improved.

The present invention relates to image encoding and decoding of image regions in units of blocks. Specifically, a plurality of components of an input tensor, including a first component and a second component, are processed in a spatial dimension in a plurality of pipelines. The processing of the first component includes dividing the first component into a first plurality of tiles in the spatial dimension. Similarly, the processing of the second component includes dividing the second component into a second plurality of tiles in the spatial dimension. The respective first plurality of blocks and the second plurality of blocks are then processed, respectively. And at least two corresponding juxtaposed blocks with different sizes are arranged in the plurality of first blocks and the plurality of second blocks. In the case of compression, the processing of the first component and / or the second component includes image encoding, rate distortion optimized quantization, and image filtering. In the case of decompression, the processing includes image decoding and image filtering.

The present invention belongs to the field of image processing technology, and specifically relates to a zero-delay panoramic video rate control method considering the propagation of time domain distortion. The method of the present invention is mainly to optimize the target bit allocation and global rate distortion optimization coding, including rate control at the coding tree unit (CTU) level and time domain global rate distortion optimization. CTU-level rate control mainly includes optimizing target bit allocation and updating rate control parameters; time domain global rate distortion optimization mainly uses the reconstruction error and motion compensation prediction error information of the encoded frame to estimate the time domain dependency of each CTU in the current encoded frame and adjust the rate distortion optimization parameters of the CTU accordingly, and at the same time, according to the process of projecting the panoramic spherical graphic onto the 2D plane (ERP projection), the characteristics of oversampling and increasing pixel redundancy will be generated at the two poles, and the coding parameters are adjusted according to the projection area change ratio. The present invention can effectively shorten the encoding time and improve the video encoding quality under the condition of a given bandwidth.

Systems and methods directed to a rate-distortion optimization process. One example is directed to a video encoding device including an electronic processor. The electronic processor is configured to obtain motion information associated with a video block and determine, as a function of the motion information, a subset of coding tools from a plurality of coding tools for rate-distortion performance evaluation of the video block.

The invention discloses a standing wave angular rate error compensation method and device, equipment and a storage medium, and relates to the technical field of error compensation, and the method comprises the steps: obtaining a two-dimensional vibration equation corresponding to a harmonic oscillator; obtaining a target standing wave angular rate error formula corresponding to the harmonic oscillator based on the two-dimensional vibration equation, the driving electrode error corresponding to the harmonic oscillator and the detection electrode error; controlling the harmonic oscillator to rotate at different target rotating speeds, acquiring a change relation of a standing wave angular rate error corresponding to the harmonic oscillator along with each target rotating speed in the rotating process, and performing error compensation on the standing wave angular rate according to a target standing wave angular rate error formula and the change relation; wherein the standing wave angular rate error comprises an error generated when the harmonic oscillator rotates under the condition that the rotating speed is not smaller than the target rotating speed. The error generated when the harmonic oscillator rotates under the condition that the rotating speed is not smaller than the target rotating speed is compensated, so that the problem of distortion of the output angle or the angular rate is solved.

Processing circuitry determines to encode one or more blocks in a current picture using cross component sample offset (CCSO), and begins to search for combinations of values of filter parameters of the CCSO, each combination of values of filter parameters comprising a value for each filter parameter, respectively. The processing circuitry determines that a first rate distortion cost associated with at least a first combination of values satisfies a condition; in response to the first rate distortion cost satisfying a condition, terminating searching for at least a second combination of values of filter parameters of the CCSO; and selecting a value of a filter parameter for performing CCSO to encode one or more blocks in the current picture based on a value combination obtained from the search, the value combination obtained from the search not including a second combination of values.

A better rate distortion ratio is achieved by making interrelationships between coding parameters of different planes available for exploitation for the aim of redundancy reduction despite the additional overhead resulting from the need to signal the inter-plane prediction information to the decoder. In particular, the decision to use inter plane prediction or not may be performed for a plurality of planes individually. Additionally or alternatively, the decision may be done on a block basis considering one secondary plane.

In one implementation, an encoder obtains a first value indicating a number of bits used to encode a current block in a picture, under a coding option, and obtains a second value indicating a distortion between a reconstructed version and an original version of the current block associated with the coding option. The encoder obtains a cost function based on the first value and the second value for the current block. The encoder also obtains another cost function for the current block, associated with a current best coding option. By comparing the cost function and the another cost function, wherein the cost function or the another cost function is scaled by a complexity factor indicating computational complexity associated with the coding option, the encoder updates the another cost function and the current best coding option based on the comparison result.

The invention provides a method and apparatus for loop filtering. The loop filtering method comprises the following steps: acquiring an MCTF (Motion Compensation Time Domain Filtering) filtered image of a current image after MCTF; determining the similarity between the MCTF filtering image and a filtering reference image when the MCTF is carried out on the current image; and determining whether to perform rate distortion optimization of loop filtering using an original image of the current image or the MCTF filtered image based on the similarity.

In various implementations, method and devices are disclosed that involves video encoding based on a Lagrangian rate-distortion cost using a Lagrangian parameter. In a variant, a set of coding modes responsive to a Lagrangian rate-distortion cost comprises an adaptive in-loop filtering mode and wherein determining an adaptive in-loop filtering mode based on a Lagrangian rate-distortion cost using a Lagrangian parameter further comprises modifying a Lagrangian parameter for determining the adaptive in-loop filtering mode.

Different implementations are described, particularly implementations for determining a set of predictor candidates for affine merge coding mode from neighboring blocks for motion compensation of a picture block based on a motion model. The motion model, may be, e.g., an affine model in a merge mode or AMVP mode for a video content encoder or decoder. The motion model, may be, e.g., an affine model based on top-left / top-right control point motion vectors or an affine model based on top-left / bottom-left control point motion vectors. Such affine model may be signaled by a flag. In an embodiment, predictor candidates are sorted in the set based on a criterion such as, e.g., a validity check or a vectors coherence cost. In an embodiment, a predictor candidate is selected from the set based on a motion model for each of the multiple predictor candidates, and may be based on a criterion such as, e.g., a rate distortion cost. The corresponding motion field is determined based on, e.g., one or more corresponding control point motion vectors for the block being encoded or decoded. The corresponding motion field of an embodiment identifies motion vectors used for prediction of sub-blocks of the block being encoded or decoded.

The invention discloses a non-additive HEVC (High Efficiency Video Coding) video steganography method based on an inter-frame distortion transmission chain. The embedding process comprises three parts of carrier extraction, distortion transmission chain construction and distortion cost updating. The method comprises the following steps: firstly, dynamically screening HEVC compressed video steganography carriers, and dividing the carriers into three classes according to position features; constructing an inter-frame distortion transfer chain based on the motion vectors of the three carriers; and finally, calculating three types of carrier embedding distortion cost values, and realizing minimum distortion path embedding based on STC coding, specifically, completing information embedding of the first type of carrier according to the initial distortion cost value, dynamically correcting the cost value of the second type of carrier through a distortion transfer chain, and completing embedding so as to realize cascade steganography. Embedding of the third type of carriers is completed in the same manner; the method has the advantages that the sampling point distortion change caused by inter-frame distortion transfer is reflected by constructing the space-time coupled inter-frame distortion transfer chain, the inter-frame distortion drift is inhibited, the steganography rate distortion fluctuation is reduced, the visual quality is improved, the bit rate increase is reduced, and the security is enhanced.

The application discloses a video compression transmission method and related equipment, the method comprises the following steps: obtaining a video sequence to be compressed, taking the first frame and the last frame as conditional frames; inputting the video sequence into the encoder of a pre-trained variational autoencoder to obtain a target latent space representation; processing the target latent space representation through the downsampling module of the compressor to generate an extreme compression representation; transmitting the conditional frames and the extreme compression representation to the receiving end to enable the receiving end to reconstruct the video through the upsampling module of the compressor, the generation model and the decoder of the variational autoencoder to obtain a reconstructed video sequence; the application provides time sequence boundary information through the conditional frames, and in combination with the reconstruction capability of the generation model, can effectively reduce the block effect, blur and high-frequency detail loss commonly seen in traditional methods; the conditional frames and the extreme compression representation significantly reduce the transmission code rate and bandwidth demand, can significantly improve the rate distortion performance, and can be widely applied to the technical field of video compression.

This invention discloses deep learning-based video compression using optimized rate distortion. Systems and methods are provided for enhancing image patches of frames in a video to be compressed. These systems and methods enhance image patches to improve the compression of the video. In at least one embodiment, systems and methods are provided for enhancing video content using a learnable pre-filtering network trained with a joint loss function to improve compression.