Alternative methods for codebook design in vector quantization

Authors:
V. Delport
Affiliations:
-
Venue:
DCC '95 Proceedings of the Conference on Data Compression
Year:
1995

Citing 2
Cited 0

Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms

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Abstract

A vector quantizer maps a multidimensional vector space into a finite subset of reproduction vectors called a codebook. For codebook optimization the well known LBG algorithm or a simulated annealing technique are commonly used. Two alternative methods the fuzzy-c-mean (FCM) and a genetic algorithm (GA) are proposed. In order to illustrate the algorithm performance a DCT-VQ has been chosen. The fixed partition scheme based on the mean energy per coefficient is shown for the test image "Lena".