In this paper, a novel algorithm called a non-local adaptive mean filter (NAMF) for removing salt-and-pepper (SAP) noise from corrupted images is presented. We employ an efficient window detector with adaptive size to detect the noise, the noisy pixel will be replaced by the combination of its neighboring pixels, and finally we use a SAP noise based non-local mean filter to reconstruct the intensity values of noisy pixels. Extensive experimental results demonstrate that NAMF can obtain better performance in terms of quality for restoring images at all levels of SAP noise.

翻译：本文展示了一种叫作非本地适应性平均过滤器(NAMEF)的小说算法(NAMEF ), 用于从被腐蚀的图像中去除盐和椒(SAP)噪音。 我们使用一个有适应性大小的高效窗口探测器来检测噪音, 噪音像素将被其邻近像素的组合所取代, 最后我们用一个基于SAP的噪音的非本地平均过滤器来重建噪音像素的强度值。 广泛的实验结果表明,NAF在恢复SAP各级噪音图像的质量方面可以取得更好的表现。