摘要
本文描述了一种基于自适应遗传算法的图象矢量量化方法，它不同于一般遗传算法之处是其交叉概率与变异概率这两个参数随个体的适应度值而变化，从而增强了算法的性能。实验结果表明，将自适应遗传算法用于码本设计，具有运算简单、聚类能力强等优点，有着广泛的应用前景。
This paper presents a new approach to image compression using vector quantization (VQ) technique and adaptative genetic algorithm (AGA). The difference between AGA and standard genetic algorithim(SGA) is that the probabilities of crossover and mutation of the former are varied depending on the fitness values of the solutions. Thus improving the performance of the algorithms. Experimental results show that applying AGA to image VQ codebook design is computationally simpler and has a strong clustering ablility, and can be used in many fields.
出处
《电脑与信息技术》
1998年第3期6-8,共3页
Computer and Information Technology
关键词
矢量量化
自适应遗传算法
图像编码
Vector quantization Adaptative Genetic Algorithm Clustering Adaptation fuction
