DocumentCode :
1871787
Title :
Design of vector quantization codebooks using a genetic algorithm
Author :
Zheng, Xiaowei ; Julstrom, Bryant A. ; Cheng, Weidong
Author_Institution :
Business Transactions Express Inc., Saint Cloud, MN, USA
fYear :
1997
fDate :
13-16 Apr 1997
Firstpage :
525
Lastpage :
529
Abstract :
Data compression techniques recode data into more compact forms. One such technique is vector quantization, which maps groups of input symbols, called vectors, onto a small set of vectors, called the codebook. Each vector in the codebook is a codeword. The indexes of the codewords represent the original vectors, and writing the codewords that the indexes indicate restores a facsimile of the original data. The similarity of the restored data to the original under vector quantization depends on the codebook, and several algorithms have been proposed for designing it from a training set of typical vectors. This paper describes a genetic algorithm for the problem of codebook design. The genetic algorithm´s chromosomes represent partitions of the training set; each vector maps to the codeword that is the centroid of its set in the partition. To speed up its operation, the genetic algorithm uses fitness inheritance to assign fitness values to most new chromosomes, rather than evaluating them. Tests using five standard digitized images compare the genetic algorithm to a popular non-genetic algorithm for codebook design. The genetic algorithm is found to be effective, but slow
Keywords :
genetic algorithms; image coding; image restoration; vector quantisation; centroid; chromosomes; codeword indexes; data compression; data facsimile restoration; fitness inheritance; genetic algorithm; input symbols; nongenetic algorithm; standard digitized images; training set partitions; vector quantization codebook design; Algorithm design and analysis; Biological cells; Data compression; Facsimile; Genetic algorithms; Image restoration; Partitioning algorithms; Testing; Vector quantization; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 1997., IEEE International Conference on
Conference_Location :
Indianapolis, IN
Print_ISBN :
0-7803-3949-5
Type :
conf
DOI :
10.1109/ICEC.1997.592366
Filename :
592366
Link To Document :
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