CTH04-2: A Multiple-Description Trellis Quantizer for Sources With Memory

Abstract

An approach to multiple description block quantization of a correlated source for transmission over a lossy communication channel is presented. The main idea is to optimally control the redundancy due to both the quantizer index assignment and the residual temporal correlation within a block of quantizer outputs. This is achieved by using a trellis encoder in which each state has an associated index assignment, a finite-state central decoder, and a set of Markov-model based side-decoders which exploit the encoder residual redundancy to reconstruct the source based on an incomplete set of descriptions. An iterative descent algorithm is presented for optimizing the proposed coding system for source statistics and channel loss probability. Simulation results are given which demonstrate the performance of trellis quantizers designed for a Gauss-Markov source.