期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：8
页码：385-394
DOI：10.14257/ijsip.2015.8.8.39
出版社：SERSC
摘要：It is hard to segmentation brain MR images for the bias fields. In this paper, a new fuzzy anisotropic diffusion function is presented to reduce the effect of the noise. We use Legendre polynomial functions to reconstruct the bias field, which make the entropy of the recovered image be smallest. But it needs to compute a lot of parameters to reconstruct the bias. The traditional method uses the gradient descending method to compute the parameters. The method plunges into local best easily. In order to deal with this problem, Particle swarm optimization (PSO) method is analyzed. A new particle swarm technique is proposed that incorporates initial location information and use mutate operation make the particles away from local maxima. The experiments show that the new method can get accurate result robustly
关键词：fuzzy anisotropic diffusion; entropy; genetics algorithm; Particle swarm ; optimization; local maxima; global maxima
