计算机工程与科学2017，Vol.39Issue(6)：1133-1140,8.DOI:10.3969/j.issn.1007-130X.2017.06.017
椒盐噪声图像的非局部平均滤波算法
A nonlocal means filter for images with salt-and-pepper noise
摘要
Abstract
According to the fact that the nonlocal means (NLM) method cannot adequately remove noise from the images corrupted by salt-and-pepper noise,we extend the NLM to remove salt-and-pepper noise by introducing the noise detection results.At the noise detection stage,we divide pixels into two categories:noisy and noise-free pixels,depending on two extreme values Lmin and L At the filtering stage,noise-free pixels remain unchanged,while for each noise pixel,if the adaptive filtering window does not contain any noise-free pixel,we regard the current noise pixel located in image uniform regions composed of noise-free pixels with the same gray value Lmin or L And then the calculated statistics is used as the restored value.Otherwise,we employ the improved NLM filter for noise removal.The joint noise detection mask in the proposed method can avoid the influence of noise pixels on calculating similar weights in the presence of noise pixels,and only noise-free pixels are used for the weighted average.In addition,the iterative filtering scheme is used to remove noise of high-density.Experimental results demonstrate the effectiveness of the proposed filter even though its computational complexity is still high.关键词
图像去噪/椒盐噪声/非局部平均/相似权/迭代滤波Key words
image denoising/salt-and-pepper noise/nonlocal means/similarity weight/iterative filtering分类
信息技术与安全科学引用本文复制引用
许光宇,蒋社想..椒盐噪声图像的非局部平均滤波算法[J].计算机工程与科学,2017,39(6):1133-1140,8.基金项目
国家自然科学基金(61471004) （61471004）
安徽理工大学青年教师科学研究基金(QN201322) （QN201322）
安徽理工大学博、硕士基金(ZX942) （ZX942）
