A generalized multistage VQ approach for spectral magnitude quantization

Abstract

This paper presents a novel vector quantization (VQ) technique in which the quantized vector is formed by adding the transformed outputs of a multistage codebook rather than just adding the outputs of the stages as in regular multistage vector quantization (MSVQ). The transformations are selected from a family of linear transformations represented by a codebook of matrices. This technique can be viewed as a generalized form of MSVQ. If the transformations are constrained to be the identity transformation, this technique becomes identical to the regular MSVQ. The design algorithm is based on joint optimization of the linear transformations and the stage codebooks. It is shown that the proposed technique yields high quality spectral magnitude quantization with performance exceeding that of multistage vector quantization (MSVQ) of similar complexity and bit rate.