计算机科学 ›› 2012, Vol. 39 ›› Issue (7): 280-281.
• 图形图像 • 上一篇 下一篇
陈倩
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摘要: 矢量量化在图像压缩中有着举足轻重的地位。码书的设计是算法的关键,经典的LI3G聚类算法由于对初始码书的选择非常敏感会导致不同的量化效果。把遗传算法和L13G算法相结合,充分利用LBG算法的局部搜索能力和遗传算法的全局寻优能力,能够在大大改善码本质量的同时加快算法的收敛速度。
关键词: 图像矢量量化,LI3G聚类算法,遗传算法
Abstract: Vector quantization is a very important image compression algorithm and its key is the design of codebook.The classic LI3G clustering algorithm results in different performance because of sensitive selection of the initial cluster center. This paper applied LI3(;clustering algorithm into genetic algorithm to optimize cluster center, which uses the advantages of high local search ability of I_I3G and global optimization ability of GA. hhe hybrid method can not only improve the duality of codebook but also speed algorithm convergence.
Key words: Image vector quanti}ation, I_BG clustering algorithm, Genetic algorithm
陈倩. 基于遗传LBG的图像矢量量化改进算法[J]. 计算机科学, 2012, 39(7): 280-281. https://doi.org/
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