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基于Log-Gabor特征的非局部均值去噪算法及其加速方案研究*

DOI: 10.16451/j.cnki.issn1003-6059.201503011, PP. 266-274

Keywords: 非局部均值,Log-Gabor特征,混合相似度,Johnson-Lindenstrauss引理,随机降维

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Abstract:

非局部均值是一种基于像素长程相似性的图像空域去噪算法,它一般采用灰度块特征估计图像像素间的相似度.文中首先使用基于Log-Gabor特征的像素间相似度估计获得较好的去噪效果.然后将Log-Gabor几何特征与灰度特征相融合,所形成的混合相似度具有更佳的图像局部自适应性,去噪性能也得到进一步提升.最后基于Johnson-Lindenstrauss引理研究利用随机降维方法降低相似度计算的复杂度,并对该加速方案的效果,包括降维前后运行时间对比、降维程度以及随机矩阵生成方法对去噪性能的影响,进行详细试验分析,结果证明基于随机降维的加速方案的有效性.

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