Salt-and-pepper noise removal based on nonlocal mean filter

Xunbo Yin, Jiaqi Zhu
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引用次数: 1

Abstract

In this paper, a new two-phase method for salt-and-pepper noise removal is proposed which combines the adaptive median filter and nonlocal mean filter. In the first phase, the adaptive median filter is used to identity pixels which are likely to be contaminated by noise. In the second phase, the image is restored using the nonlocal mean filter which is firstly proposed for Gaussian noise removal. It has a strong ability to handle textures and repetitive structures. Experimental results show that the proposed algorithm achieved not only high PSNR but also pleasure visual results even when the noise level is high as 90%.
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基于非局部均值滤波的椒盐噪声去除
本文提出了一种结合自适应中值滤波和非局部均值滤波的两相椒盐噪声去除方法。在第一阶段,使用自适应中值滤波器来识别可能被噪声污染的像素。在第二阶段,使用非局部均值滤波器对图像进行恢复,该滤波器首次被提出用于高斯噪声的去除。它有很强的处理纹理和重复结构的能力。实验结果表明,在噪声水平高达90%的情况下,该算法不仅具有较高的PSNR,而且具有良好的视觉效果。
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