摘要
阐述了一种有效的基于遗传算法和迭代函数系统(IFS)的二值图像压缩的基本思想和实现算法。同时,根据现有的并行遗传算法的框架,实现了一种基于遗传算法的异构分布式并行分形图像压缩基本模型算法,并在此基础上提出了复杂模型的设计方案。理论分析及实验结果表明,该分布式并行算法有较强的搜索能力,算法效率、可移植性较高,能找到近似最优的IFS解,其解码图像十分相似于原图像,并有很高的图像质量及压缩比。
An effective approach of the fractal binary image compression was presented based on genetic algorithm and IFS（ Iterated Function System）. And then, a heterogeneity distributed version of the binary fractal image compression algorithm was implemented according to the existent distributed or parallel framework. In addition, designed scheme of a sophisticated distributed model was elaborated. Both the oretical analysis and experiment results show that the proposed algorithm has tremendous ability in searching best solutions, and can find out one of the most approximate result of IFS whose decoding image is quite similar with original one, and also has a higher compression ratio with high quality image.
出处
《计算机应用》
CSCD
北大核心
2006年第4期793-796,共4页
journal of Computer Applications
基金
上海市重点学科建设资助项目(P1303)
关键词
图像压缩
迭代函数系统
遗传算法
分形
分布式
并行
image compression
Iterated Function System（IFS）
genetic algorithm
fractal
distributed
parallel
