Zero-Delay Multiple Descriptions of Stationary Scalar Gauss-Markov Sources

In this paper, we introduce the zero-delay multiple-description problem, where an encoder constructs two descriptions and the decoders receive a subset of these descriptions. The encoder and decoders are causal and operate under the restriction of zero delay, which implies that at each time instance, the encoder must generate codewords that can be decoded by the decoders using only the current and past codewords. For the case of discrete-time stationary scalar Gauss—Markov sources and quadratic distortion constraints, we present information-theoretic lower bounds on the average sum-rate in terms of the directed and mutual information rate between the source and the decoder reproductions. Furthermore, we show that the optimum test channel is in this case Gaussian, and it can be realized by a feedback coding scheme that utilizes prediction and correlated Gaussian noises. Operational achievable results are considered in the high-rate scenario using a simple differential pulse code modulation scheme with staggered quantizers. Using this scheme, we achieve operational rates within 0.415 bits / sample / description of the theoretical lower bounds for varying description rates

Multiple description coding with prediction compensation

A new multiple description coding paradigm is proposed in this dissertation, by combining the time domain lapped transform, block level source splitting, inter-description prediction, and coding of the prediction residual. The joint design of all system components is developed, and the asymptotic performance in the DPCM case for first-order Gauss-Markov sources is analyzed. Image coding results show that the proposed method can significantly outperform other methods in the literature. The effects of different transforms and the size of the prediction filter are also studied. A number of generalizations of the proposed scheme is studied as well. First, the two dimensional Wiener filter is introduced into this scheme. These filters can improve the performance when the redundancy is low. Secondly, the proposed scheme is extended to three-description and four-description cases. The optimal design and image coding results are reported