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一种基于遗传算法的图像矢量量化方法

Image VQ Coding Using Genetic Algorithm
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摘要 描述了一种基于遗传算法的图像矢量量化方法。遗传算法基于自然进化原理可得到全局优化结果,把遗传算法用于码本设计,运算简单,而且可避免传统方法如K-均值技术等所带来的局部优化局限。同时,由于其结构的规则性和并行性,较适于VLSI实现。文中主要讨论了遗传算法用于图像矢量量化的适应度函数及操作过程,并与传统算法作了比较,最后给出了实验结果。 This paper presents a new appr oach to image compression using vetor quantization(VQ) technique and genetic al g orithm(GA).GA is an optimal algorithm which comes from the priciple of natural p rocess. By using GA for image VQ codebook design, it is found that GA is more ro bust in locating the global optimum and is computationally simpler than other al gorithms such as K means. Because of its regularity and high parallelism in s tructure, this method is also suitable for VLST implementation. The adaptation f unction and operation process of GA used for image VQ are discussed in detail, i ts performance is evaluated through some experiment results.
出处 《微机发展》 1998年第3期57-59,共3页 Microcomputer Development
关键词 图像压缩 矢量量化 遗传算法 图像编码 Image Compression Vector Qua ntization Genetic Algorithm Adaptation Function
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