Next-state functions for finite-state vector quantization

Abstract

The finite-state vector quantization scheme called dynamic finite-state vector quantization (DFSVQ) is investigated with regard to its subcodebook construction. In the DFSVQ, each input block is encoded by a small codebook called the subcodebook which is created from a much larger codebook called supercodebook. Each subcodebook is constructed by selecting, using a reordering procedure, a set of appropriate code-vectors from the supercodebook. The performance of the DFSVQ depends on this reordering procedure; therefore, several reordering procedures are introduced and their performance are evaluated. The reordering procedures investigated, are based on the conditional histogram of the code-vectors, index prediction, vector prediction, nearest neighbor design, and the frequency usage of the code-vectors. The performance of the reordering procedures are evaluated by comparing their hit ratios (the number of blocks encoded by the subcodebook) and their computational complexity. Experimental results are presented and it is found that the reordering procedure based on the vector prediction performs the best when compared with the other reordering procedures.