摘要
为了降低图像存储、传输的空间复杂度,必须对图像进行压缩。为此,研究如何将量子行为的粒子群优化算法(QPSO)运用于图像压缩。在图像的压缩处理中,先对原始图像元素序列进行排序,再根据收敛性要求对压缩编码进行优化。实验结果表明该算法压缩效果优于经典遗传算法(GA)。
In order to decrease the space complexity of image storage and transfer, it is necessary to do image compression. Therefore, how to apply Quantum-behaved Particle Swarm Optimization（QPSO） to image compression was studied in this paper. During the compression process, an ordered representation of image was first obtained, and then the compressed code was optimized according to the particles astringency. Experimental results show that the compression efficiency of QPSO algorithm is much better than Genetic Algorithm （ GA）.
出处
《计算机应用》
CSCD
北大核心
2006年第10期2369-2371,共3页
journal of Computer Applications
基金
国家自然科学基金资助项目(60474030)
关键词
基于量子行为的粒子群优化算法
遗传算法
图像压缩
Quantum-behaved Particle Swarm Optimization （QPSO） algorithm
Genetic Algorithm （GA）
image compression
