The design of generalized product-code vector quantizers

Abstract

Structured vector quantization (VQ) can achieve superior performance-complexity tradeoffs in comparison with unstructured VQ. Many VQ schemes fall into a class of structured VQ called product codes. A generalization of product codes wherein a feature may have multiple codebooks is considered. For the design of generalized product codes (GPCs) methodologies are devised for achieving independent tradeoffs of codebook storage complexity and encoding complexity versus distortion performance and for the joint optimization of feature codebooks. This GPC design framework makes it possible to attain many intermediate levels of rate-distortion performance between unstructured VQ and conventional product codes. Thus, the performance of unstructured VQ may be approached with a lower-complexity GPC. The framework is illustrated using numerical results from the quantization of speech line-spectral frequency parameters.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>