Low-Complexity Joint Source Channel Decoding of Image
低复杂度的图像信源-信道联合译码算法

Markov Random Field Model (MRFM) is separated into four Markov chains which are used to represent the residuals of encoded image source. Combined with the soft output of Low Density Parity Check (LDPC) code, this simplified model is used in joint source channel decoding. Different correlation in different direction in source is regarded as a kind of “natural” channel code. In order to utilize the correlation, a serial decoding using forward-backward algorithm and a parallel decoding using sum-product algorithm are proposed respectively. Simulations show that compared with the traditional joint source channel decoding algorithm based on the MRFM, the proposed algorithm has lower complexity and better PSNR of the rebuilt images.