Joint source-channel decoding method for video/image transmission

Abstract

The invention discloses a joint source-channel decoding method for video/image transmission, which is applicable to video transmission of a video coding standard H.264 and HEVC (high efficiency video coding), and image transmission of JPEG2000 (joint photographic experts group). Two modules (namely, a joint source-channel arithmetic-code decoder and a joint source-channel variable-length-code decoder) are mainly used in the method disclosed by the invention; decoding information outputted by the joint source-channel arithmetic-code decoder can be used as input information of the joint source-channel variable-length-code decoder, and then an optimal decoding symbol sequence is obtained through carrying out further searches on cellular pictures of joint variable length codes; and meanwhile, at the joint source-channel arithmetic-code decoder part, invalid search paths can be deleted by using the codon structure information of the variable length codes, thereby improving the decoding performance. The method is low in computing complexity and small in time delay, and therefore the method is applicable to actual video and image transmission systems.

Description

technical field [0001] The invention relates to a method in the technical field of video and image communication, in particular to a source channel joint decoding method for video image transmission. Background technique [0002] In traditional communication systems, source coding and channel coding are performed separately. This design principle is based on Shannon's theory of source-channel separation. But in practical systems, especially in multimedia transmission systems, due to the limitation of delay and complexity, separate systems cannot guarantee the optimality of the system. Therefore, in order to improve the system performance, people focus on the source channel joint codec. [0003] In recent years, the video compression standard H.264 has been widely used, and the standard of the new generation video compression technology HEVC is also being formulated. Their entropy coding is the context-based arithmetic code CABAC. Due to the good compression performance of...

AI Technical Summary

Problems solved by technology

[0004] There are two steps in the compression of CABAC. The first step is to binarize the symbols to be compressed. The binarization adopts unary encoding, truncated unary encoding, k-order Exp-Golomb encoding, etc. The symbol sequence is in binary After being converted, it is sent to the context-based binary arithmetic code (CABAC) encoder, and the bit sequence encoded by the binary arithmetic code is sent to the noise channel after modulation. At the receiving end, Salma Ben et al. in "IEEE trans on communication "(IEEE Transactions on Communication), 2009, Volume 57, Issue 7, pp.2014-2023 published a paper titled "improved sequential MAP estimation of CABAC encoded data with objective adjustment of the complexity / efficiency tradeoff". The joint source-channel decoder based on the maximum a posteriori probability (MAP) of the binary arithmetic part of CABAC, but she did not consider applying the joint decoding strategy to the debinarization processor. As a result, once the arithmetic from CABAC There is an error in the data from the code joint decoder, and when the symbol sequence is decoded by an ordinary inverse binarization processor, the error will spread and cause serious errors

In fact, the commonly used video standards H.264, HEVC, and image compression standard JPEG2000 all convert the symbol sequence to be compressed into a binary sequence before doing arithmetic coding, and then do binary arithmetic code coding, and the binary sequence Conversion is a process of variable length code encoding. The current joint arithmetic and digital decoding only considers the part of arithmetic and digital joint decoding. In video and image processing, variable length code decoding is usually required after arithmetic decoding. The process is not involved

Images