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一种改进的快速独立分量分析算法及其在图象分离中的应用

DOI: 10.11834/jig.2003010410

Keywords: 计算机图象处理(520?6040),独立分量分析,固定点算法,FastICA,M-FastICA,图象分离

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Abstract:

独立分量分析是信号处理技术的新发展,它作为盲信号分离的一种有效的方法而受到广泛的关注,并在许多方面获得成功应用.讨论了独立分量分析的基本原理、判断条件和算法,并在此基础上,介绍了独立分量分析的一种快速算法――FastICA算法;对FastICA算法的核心迭代过程进行改进,得到M-FastICA算法,改进算法减少了独立分量分析的迭代次数,从而提高了算法的收敛速度.最后将M-FastICA算法应用到图象的分离上,实验结果表明,改进算法在分离效果相当的前提下,串行算法迭代次数减少了9%,并行算法迭代次数减少了27%,收敛速度更快.

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