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30 results about "Multiple description coding" patented technology

Multiple description coding (MDC) is a coding technique that fragments a single media stream into n substreams (n ≥ 2) referred to as descriptions. The packets of each description are routed over multiple, (partially) disjoint paths. In order to decode the media stream, any description can be used, however, the quality improves with the number of descriptions received in parallel. The idea of MDC is to provide error resilience to media streams. Since an arbitrary subset of descriptions can be used to decode the original stream, network congestion or packet loss — which are common in best-effort networks such as the Internet — will not interrupt the stream but only cause a (temporary) loss of quality. The quality of a stream can be expected to be roughly proportional to data rate sustained by the receiver.

Semantic segmentation combined multi-description coding method and system

The invention discloses a semantic segmentation combined multi-description coding method and system. The semantic segmentation combined multi-description coding method comprises the steps that an original image and a corresponding semantic segmentation label serve as input to be transmitted to a multi-description feature generation network; the multi-description feature generation network generates two similar but not completely same descriptions by using the image context features; the generated two descriptions respectively enter a semantic segmentation coding network to be coded, and in thecoder, the descriptions are firstly up-sampled into an up-sampled image consistent with an original image in size, and then the up-sampled image and semantic segmentation mapping pass through a generation network together to generate a residual image, and the residual image and pixels of the up-sampled image are added to obtain a coarse reconstructed image; and the generated coarse reconstructedimage is transmitted to the multi-description decoding network through an information channel, and the semantic segmentation label is encoded by the standard encoder and then is transmitted to the multi-description decoding network, and a final reconstructed image is obtained through decoding. The consequence that the image reconstruction quality is not ideal due to the packet loss problem in thetransmission process is avoided, and the coding efficiency is better improved.
Owner:SHANDONG NORMAL UNIV

Multi-description compressed image enhancement method based on residual recursion compensation and feature fusion

ActiveCN113362225AAvoid the phenomenon of fittingReduce the amount of learnable parametersImage enhancementGeometric image transformationImaging qualityCompression artifact
The invention discloses a multi-description compressed image enhancement method based on residual recursion compensation and feature fusion, belongs to the field of image quality enhancement, and solves the problem of different degrees of compression distortion of an image compressed by a multi-description coding method, especially the problem of serious structure splitting artifacts of a side decoded image. The method comprises the following steps: firstly, designing a residual recursive compensation network as a low-resolution feature extraction network of a side path and a middle path, and more effectively extracting two description decoding image features with the same content and different details by using a parameter sharing strategy; secondly, enabling the multi-description side feature up-sampling reconstruction network to adopt a network part layer parameter sharing strategy, so that the size of a network model is greatly reduced, and the generalization ability of the network is improved. Meanwhile, a multi-description middle-path feature up-sampling reconstruction network is used for performing deep feature fusion on two side-path low-resolution features and a middle-path low-resolution feature, so that efficient multi-description compressed image quality enhancement is realized, and the performance of the method is superior to that of a plurality of deep learning image enhancement methods such as ARCNN, FastARCNN and DnCNN.
Owner:TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY

Time domain overlap transformation multi-description coding and decoding method and system based on JND (Just Noticeable Difference)

The invention relates to a time domain overlap transformation multi-description coding and multi-description decoding method and system based on JND (Just Noticeable Difference). The multi-description coding method comprises the steps of obtaining image information, dividing the image information into two subsets: a first subset and a second subset, generating a first description and a second description at the same time, wherein the two descriptions comprise the first subset and the second subset at the same time; for the first description, on the basis of a multi-description method, predicting the second subset through adoption of the first subset, carrying out entropy coding according to the first subset and a prediction value of the second subset, and outputting a first multi-description code stream; and for the second description, on the basis of the multi-description method, predicting the first subset through adoption of the second subset, carrying out entropy coding according to the second subset and the prediction value of the first subset, and outputting a second multi-description code stream, wherein the multi-description method comprises the step of carrying out time domain-based overlap transformation, DCT, JND-based threshold filtering and quantization processing on the two subsets in sequence.
Owner:SHANDONG NORMAL UNIV

Multi-description coding method, multi-description decoding method and multi-description coding and decoding system based on KSVD (K singular value decomposition)

The invention discloses a multi-description coding method, a multi-description decoding method and a multi-description coding and decoding system based on KSVD (K singular value decomposition). The multi-description coding method comprises the steps of obtaining image information, dividing the image information into two subsets: a first subset and a second subset, and generating first descriptionand second description, wherein the two pieces of description comprise the first subset and the second subset at the same time; for the first description, on the basis of a multi-description method, predicting the second subset through adoption of the first subset, carrying out entropy coding according to the first subset and a predicted value of the second subset, and outputting a first multi-description bit stream; and for the second description, on the basis of the multi-description method, predicting the first subset through adoption of the second subset, carrying out entropy coding according to the second subset and the predicted value of the first subset, and outputting a second multi-description bit stream, wherein the multi-description method comprises the step of carrying out timedomain-based lapped transform, KSVD transform and quantization processing on the two subsets in sequence.
Owner:SHANDONG NORMAL UNIV

An Error Recovery Method for Spatial Domain Multiple Description Coding

The invention discloses an error concealment method of space-domain MDC (Multiple Description Coding). The error concealment method comprises the following steps of (1) inputting an original streaming video, and decoding the original streaming video by adopting the space-domain MDC having two descriptions; and (2) carrying out error detection on the two descriptions of the original streaming video, and judging as follows when one description is lost: a, carrying out concealment of motion information on the losing part if the losing part has time-domain correlation; b, carrying out the concealment on the losing part by adopting a space-domain interpolation method if the losing part has space-domain correlation; and c, comparing the time-domain distortion degree of the losing part with the space-domain distortion degree of the losing part: carrying out the concealment by adopting the method of step a if the time-domain distortion degree is less than the space-domain distortion degree, and carrying out the concealment by adopting the method of step b if the time-domain distortion degree is larger than or equal to the space-domain distortion degree. According to the error concealment method provided by the invention, the error concealment performance of the space-domain MDC can be enhanced.
Owner:ZHEJIANG UNIV

Method and system for multi-description encoding and decoding of time-domain lapped transform based on jnd

The invention relates to a time domain overlap transformation multi-description coding and multi-description decoding method and system based on JND (Just Noticeable Difference). The multi-description coding method comprises the steps of obtaining image information, dividing the image information into two subsets: a first subset and a second subset, generating a first description and a second description at the same time, wherein the two descriptions comprise the first subset and the second subset at the same time; for the first description, on the basis of a multi-description method, predicting the second subset through adoption of the first subset, carrying out entropy coding according to the first subset and a prediction value of the second subset, and outputting a first multi-description code stream; and for the second description, on the basis of the multi-description method, predicting the first subset through adoption of the second subset, carrying out entropy coding according to the second subset and the prediction value of the first subset, and outputting a second multi-description code stream, wherein the multi-description method comprises the step of carrying out time domain-based overlap transformation, DCT, JND-based threshold filtering and quantization processing on the two subsets in sequence.
Owner:SHANDONG NORMAL UNIV
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