A recursive side-decoder for multiple description quantization

Theoretically, the achievable side-distortion of a multiple description (MD) quantizer has a lower bound for a given level of central distortion, but such rate-distortion bounds cannot be achieved in practice. The paper presents a new decoder which exploits the residual redundancy in a sequence of outputs from a sub-optimal MD encoder to reduce side-distortion, without compromising central distortion. A hidden Markov model-based recursive side-decoder is derived for the reconstruction of a source from an incomplete set of descriptions. Simulation results based on encoding a Gauss-Markov source and a simulated speech process are presented to demonstrate the effectiveness of the proposed decoder.