摘要
传统图像压缩算法存在图像压缩率不高、寻找最优分形图像压缩编码速度慢的不足。为此,提出一种基于基因表达式编程(GEP)的分形图像压缩并行算法。分析二值图像压缩变换的求解过程,给出分形图像基因和染色体的编码表示,设计适应度函数,研究GEP遗传进化操作的编码步骤。在PC机群上的实验结果表明,与串行算法相比,该算法的图像压缩率较高、运行速度较快,具有线性加速比。
Image compression rate is not high at present and global search or genetic algorithm has slow speed to find the optimal fractal image compression coding.The fractals image compression parallel algorithm based on Gene Expression Programming（GEP） is proposed.Binary fractal image compression process of solving Iterated Function System（IFS） is analyzed.The gene and chromosome coding express of fractal image compression,the fitness function and genetic evolution operating of select,mutating,insert string,gene transformation,gene recombination are given.The fractals image compression parallel algorithm based on GEP is structured.Experimental results show that the algorithm has higher compression ratio,and running velocity faster than sequence algorithm on PC cluster,it has a linear speedup ratio.
出处
《计算机工程》
CAS
CSCD
2012年第7期201-202,共2页
Computer Engineering
基金
国家自然科学基金资助项目(61163012)
2009年度广西教育厅科研基金资助项目(200911MS144)
关键词
分形图像
压缩编码
基因表达式编程
并行算法
加速比
fractals image
compression coding
Gene Expression Programming（GEP）
parallel algorithm
speedup ratio
