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Genetic algorithm with deterministic crossover for vector quantization
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DOI：10.1016/S0167-8655(99)00133-6.png)
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Abstract
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Genetic algorithm (GA) provides high quality codebooks for vector quantization (VQ) at the cost of high running time. The crossover method is the most important choice of the algorithm. We introduce a new deterministic crossover method based on the pairwise nearest neighbor method. We show that high quality codebooks can be obtained within a few minutes instead of several hours as required by the previous GA-based methods. The method outperforms all comparative codebook generation methods in quality for the tested training sets. (C) 2000 Elsevier Science B.V. All rights reserved.
Keywords:
vector quantization
codebook generation
clustering
genetic algorithms
combinatorial optimization
image compression
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