DPCM picture transmission over noisy channels with the aid of a Markov model

The problem of DPCM picture transmission over noisy channels is considered. It is well known that DPCM systems are very sensitive to channel errors. The goal in this work is to build robustness against channel errors. Three methods are proposed in this paper and are obtained by modeling the encoded signal as a Markov sequence. First, an optimum method for decoding correlated sequences is derived, and it is shown to require Viterbi decoding. Then, a modified MAP method (MMAP) for Markov sequences is described. A maximal signal-to-noise (MSNR) receiver for DPCM systems is also developed that minimizes the distortion power due to channel errors. The appropriate cost matrix for this receiver is computed. These methods are applied to DPCM picture transmission over noisy channels and are compared with a another method. The SNR graphs, as well as subjective examination of the received pictures, demonstrate that the proposed procedures are quite effective and superior to that method. Among the proposed methods, the MSNR receiver was found to be more effective than the others for a given order of the Markov model. It is observed that the proposed methods are most beneficial for low detail pictures.