Codebook Design Optimization Based on Estimation of Distribution Algorithms

Author

Dong, Jiwen ; Guo, Ying

Author_Institution

Dept. of Inf. Sci. & Eng., Univ. of Jinan, Jinan

Volume

5

fYear

2008

fDate

18-20 Oct. 2008

Firstpage

481

Lastpage

484

Abstract

Vector quantization has been a very important technique for compressing both the image and the speech data. One of the key problems arising in vector quantization is the codebook design problem. In this paper, use estimation of distribution algorithms (EDAs) to optimize codebook design. EDAs are evolutionary computation, combined by genetic algorithm and statistically learning. In order to verify the EDAs performance, compare the EDAs with LBG and GA. The experiment results show that the EDAs make better performance on improving the codebook quality.

Keywords

codes; estimation theory; genetic algorithms; vector quantisation; codebook design optimization; codebook quality; estimation of distribution algorithm; evolutionary computation; genetic algorithm; statistically learning; vector quantization; Algorithm design and analysis; Design optimization; Electronic design automation and methodology; GSM; Genetic algorithms; Image coding; Information science; Signal generators; Speech; Vector quantization; EDAs; codebook design; vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2008. ICNC '08. Fourth International Conference on

Conference_Location

Jinan

Print_ISBN

978-0-7695-3304-9

Type

conf

DOI

10.1109/ICNC.2008.438

Filename

4667481