Universal Multiple Description Scalar Quantization: Analysis and Design

Chao Tian, Sheila S. Hemami

Abstract: A new high-rate analysis of the entropy-constrained multiple description scalar quantizer (ECMDSQ) is introduced. The analysis provides insight into the structure of the ECMDSQ, suggesting the non-optimality of uniform central quantizer cells with finite diagonals in the index assignment matrix, as well as a method to approximate optimal cell sizes. Based on these insights, a universal multiple description scalar quantizer (UMDSQ) is proposed which can achieve nearly the same performance as the fully optimized ECMDSQ, at much lower design complexity. The design requires selection of only two parameters, and the resulting UMDSQ can provide a continuum of trade-off points between the central and side distortions as the two parameters are varied.