摘要
信号的MP稀疏分解可以将信号分解为很简洁的近似表达形式,但因分解计算量巨大,难以满足实时性要求.人工鱼群算法具有收敛速度快、鲁棒性强等优点,将人工鱼群算法运用到信号的稀疏分解中,可以快速寻找分解过程中每一步的最佳原子,在此基础上对图像信号进行压缩.实验结果表明该解压图像具有较好的主观图像质量.
Signal sparse decomposition based on Matching Pursuit （MP） can decompose data into a compact approximate representation. Yet the enormous computing load of sparse decom- position hinders the real-time requirements. Artificial fish swarm algorithm features quick con- vergence and intense robustness. Its application in the sparse decomposition of signal is instru- mental for age signal factory. speedily locating the best atoms in every decomposing step. What follows is the im- compression. Experimental results show that quality of the decoded images is satis-
出处
《西安文理学院学报（自然科学版）》
2014年第2期74-77,共4页
Journal of Xi’an University(Natural Science Edition)
关键词
稀疏分解
人工鱼群算法
图像压缩
sparse decomposition
artificial fish swarm algorithm
image compression
