NEXT-STATE FUNCTIONS FOR FINITE-STATE VECTOR QUANTIZATION

In this paper, the finite-state vector quantization scheme called dyna mic finite-state vector quantization (DFSVQ) is investigated with rega rd to its subcodebook construction. In DFSVQ, each input block is enco ded by a small codebook called subcodebook which is created from a muc h larger codebook called supercodebook. Each subcodebook is constructe d by selecting, using a reordering procedure, a set of appropriate cod e-vectors from the supercodebook. The performance of the DFSVQ depends on this reordering procedure; therefore, several reordering procedure s are introduced and their performances are evaluated in this paper. T he reordering procedures that are investigated, are based on the condi tional histogram of the code-vectors, index prediction, vector predict ion, nearest neighbor design, and frequency usage of the code-vectors. The performances of the reordering procedures are evaluated by compar ing their hit ratios (the number of blocks encoded by the subcodebook) and their computational complexity. Experimental results are presente d and it is found that the reordering procedure based on the vector pr ediction performs the best when compared with the other reordering pro cedures.