Efficient codebook design in vector quantization by parallel simulated annealing and evolutionary selection

Author

Delport, Volker

Author_Institution

Tech. Univ. Chemnitz, Germany

fYear

1996

Firstpage

219

Lastpage

222

Abstract

Vector quantization is a technique that has been investigated and used in speech and image coding for data compression. A hybrid system of parallel simulated annealing and evolutionary selection (PSAES) is introduced to codebook design in vector quantization. It is examined for the vector space of low-order DCT coefficients and compared with local and near global optimization techniques. In addition an improved version of a fuzzy codebook design called fuzzy-to-hard-c-mean algorithm is proposed

Keywords

data compression; discrete cosine transforms; fuzzy set theory; image coding; simulated annealing; speech coding; transform coding; vector quantisation; VQ; data compression; fuzzy codebook design; fuzzy-to-hard-c-mean algorithm; hybrid system; image coding; local optimization; low-order DCT coefficients; near global optimization; parallel simulated annealing and evolutionary selection; speech coding; vector quantization; vector space; Algorithm design and analysis; Data compression; Discrete cosine transforms; Genetic algorithms; Image coding; Iterative algorithms; Simulated annealing; Space exploration; Speech coding; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Signal Processing Workshop Proceedings, 1996., IEEE

Conference_Location

Loen

Print_ISBN

0-7803-3629-1

Type

conf

DOI

10.1109/DSPWS.1996.555500

Filename

555500