Color quantization with genetic algorithms
作者： Tolga Taşdizen , Lale Akarun , Cem Ersoy
DOI: 10.1016/S0923-5965(97)00035-0
关键词: Algorithm 、 Mathematics 、 Color image 、 Linde–Buzo–Gray algorithm 、 Quantization (image processing) 、 Color quantization 、 Vector quantization 、 Genetic algorithm 、 Cluster analysis 、 Crossover
摘要: The need for quantization of color images arises because limitations image display and hardcopy, data storage transmission devices. Many the present algorithms find non-optimal solutions, giving rise to visible shifts in false contours when number colors is small. This paper describes a new approach finding optimal solutions problem using genetic algorithm. nature difficulty its formulation are discussed. Then (GAs) presented representation with this method explained. effect parameters such as mutation crossover probabilities population size on quality studied. Solutions obtained compared those heuristics K-means clustering algorithm superior results GA shown.
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