A Joint Source-Channel Decoding Method Based on Variable Length Codes and Arithmetic Codes

Abstract

The invention discloses a variable length code and arithmetic code based joint source-channel decoding method, which is applicable to video transmission of a video coding standard H.264 which is widely used currently, and also applicable to the video transmission of a new-generation compression standard HEVC (high efficiency video coding), and image transmission of JPEG2000 (joint photographic experts group). In consideration of the entropy coding characteristics of H.264, HEVC and JPEG2000, 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. Soft decoding information outputted by the joint source-channel arithmetic-code decoder can be used as soft 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. 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 joint source channel decoding method based on variable length codes and arithmetic codes. Background technique [0002] In traditional communication systems, source coding and channel coding are performed separately. This design principle is based on Shannon's source-channel separation theory. However, in actual systems, especially in multimedia transmission systems, due to the limitations of delay and complexity, a separate system cannot guarantee the optimal system. Therefore, in order to improve system performance, people have focused their attention on the source-channel joint coding and decoding. [0003] In recent years, the video compression standard H.264 has been widely used, and the new generation of video compression technology HEVC standards are also being formulated. Their entropy coding is based on the context-based arithmetic code CAB...

AI Technical Summary

Problems solved by technology

Although these error resistance methods can limit the error spread to a small time domain or space domain at the encoding layer, they cannot correct transmission errors, especially when the channel is very noisy, and the decoder may generate many error, severely degrades the quality of the reconstructed video

[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 "IEEEtrans 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", which designed a CABAC-based The joint source-channel decoder based on the maximum a posteriori probability (MAP) of the binary arithmetic part, but she did not consider applying the joint decoding strategy to the debinarization processor. As a result, once the arithmetic code from CABAC There is an error in the data from the joint decoder, and when the symbol sequence is decoded by an ordinary inverse binarization processor, the error will spread, causing 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