Multiple-cost constraints for the design of tree-structured vector quantizers

Minimizing the distortion subject to a cost constraint is fundamental in the design of tree-structured vector quantizers. Because of various competing cost measures, the use of single-cost constraints has led to undesirable results. The author studies the relationships among several cost functions and shows how multiple-cost constraints can be used to significantly improve tree design.

[1]  Toby Berger,et al.  Rate distortion theory : a mathematical basis for data compression , 1971 .

[2]  Robert M. Gray,et al.  Unbalanced tree-growing algorithms for practical image compression , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[3]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[4]  Robert M. Gray,et al.  Speech coding based upon vector quantization , 1980, ICASSP.

[5]  James A. Storer,et al.  Design and Performance of Tree-Structured Vector Quantizers , 1994, Inf. Process. Manag..

[6]  Thomas Eriksson,et al.  Vector Quantization in Speech Coding. Variable Rate, Memory and Lattice Quantization , 1996 .

[7]  James A. Storer,et al.  Optimal Pruning for Tree-Structured Vector Quantization , 1992, Inf. Process. Manag..

[8]  Eve A. Riskin,et al.  Lookahead in growing tree-structured vector quantizers , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[9]  R.M. Gray,et al.  A greedy tree growing algorithm for the design of variable rate vector quantizers [image compression] , 1991, IEEE Trans. Signal Process..

[10]  Philip A. Chou,et al.  Optimal pruning with applications to tree-structured source coding and modeling , 1989, IEEE Trans. Inf. Theory.

[11]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..