Robust Index Assignment for MDSQ Encoder Over Noisy Channels

Multiple description coding (MDC) can achieve acceptable performance with only one single correct description, and lower distortion of the source when more descriptions are received correctly. In our previous work, we assumed that because of noisy channel, bit errors were introduced into one description, but the other one was received correctly. Based on this assumption, an enhanced central decoder has been proposed to utilize the residual information between the corrupted and the correct description to reduce the distortion of the reconstructed signals. In this paper, a novel index assignment algorithm for multiple description scalar quantizer (MDSQ) encoder is developed to improve the error detection capability of the central decoder. Genetic algorithm (GA) is used to search for a suboptimal solution. The experimental results show that within a range of bit error rates (BERs), the proposed algorithm provides lower reconstruction distortion than the conventional MDSQ