基于遗传LBG的图像矢量量化改进算法  

Vector Quantization Method for Image Compression Based on GA and LBG Clustering Algorithm

作　　者：陈倩[1,2] 

机构地区：[1]东莞理工学院计算机学院,东莞523808 [2]浙江大学计算机科学与技术学院,杭州310027

出　　处：《计算机科学》2012年第7期280-281,286,共3页Computer Science

基　　金：广东省科技计划项目(2009B010900011)资助

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LBG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LBG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。Vector quantization is a very important image The classic LBG clustering algorithm results in different compression algorithm and its key is the design of codebook. performance because of sensitive selection of the initial cluster center. This paper applied LBG clustering algorithm into genetic algorittma to optimize cluster center. which uses the ad vantages of high local search ability of LBG and global optimization ability of GA. The hybrid method can not only im prove the quality of codebook but also speed algorithm convergence.

关 键 词：图像矢量量化 LBG聚类算法 遗传算法 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]