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中文摘要：
最近,非局部滤波方法已成为滤波领域的研究热点.本文深入研究了基于预选择的非局部滤波方法,指出了已有方法在提取图像片特征方面存在的不足,利用二维主成分分析（Two-dimensional principal component analysis,2DPCA）提出了一种有效的非局部滤波方法.该方法对基于预选择的非局部滤波方法的主要贡献有：1）用于提取图像片特征的面向图像片的2DPCA;2）基于相似距离直方图的相似集自动选取方法;3）相似距离权重参数局部自适应选取方法.实验结果表明,本文方法对弱梯度、人脸、纹理以及分段光滑图像均能取得较好的滤波效果.
英文摘要：
Recently,the non-local means filter has been a hot research topic in the image filtering field.The existing preselection based non-local means filters are analyzed intensively,and it is pointed out that they all have defects in terms of feature extraction from image patch.We employ two-dimensional principal component analysis（2DPCA） to extract feature from image patch and propose an efficient non-local means filter.Our contributions to the preselection based non-local means filter are：1） patch-oriented 2DPCA for extracting features from image patches;2） automatic selection of the similar sets based on the histogram of similarity distance;3） local adaptive determination of the similar weight coefficient parameter.Experimental results show that the new method can achieve better filtering results in a variety of images,such as weak gradient image,face image,texture image,and piecewise image.
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