In this paper, a non-local adaptive mean filter (NAMF) is proposed, which can eliminate all levels of salt-and-pepper (SAP) noise. NAMF can be divided into two stages: (1) SAP noise detection; (2) SAP noise elimination. For a given pixel, firstly, we compare it with the maximum or minimum gray value of the noisy image, if it equals then we use a window with adaptive size to further determine whether it is noisy, and the noiseless pixel will be left. Secondly, 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 further restore it. Our experimental results show that NAMF outperforms state-of-the-art methods in terms of quality for restoring image at all SAP noise levels.
翻译:在本文中,提出了一个非本地适应平均过滤器(NAMEF),它可以消除所有层次的盐和椒(SAP)噪音。NAF可以分为两个阶段:(1)SAP噪音探测;(2)SAP噪音消除。对于给定的像素,首先,我们将它与噪音图像的最大或最小灰色值进行比较,如果它相等的话,然后我们用一个具有适应大小的窗口进一步确定它是否吵闹,而无噪音像素将被留下。第二,噪音像素将被其相邻像素的组合所取代。最后,我们用基于SAP噪音的非本地平均过滤器来进一步恢复它。我们的实验结果表明,NAF在所有SAP噪音级别上恢复图像的质量都超过了最新技术。