高噪声率椒盐噪声污染图像滤波

针对高噪声率椒盐噪声污染的数字图像,改进了基于灰色绝对关联度的像素类型判别,可识别出离散噪声(或边缘点)、聚集噪声与非边缘点。对于离散噪声(或边缘点),采用自适应中值滤波算法进行平滑,兼顾噪声滤除和细节保存。对于聚集噪声,在去除邻域内噪声点后取剩余像素均值作为滤波结果;而对于非边缘点则直接保留。实验结果表明,滤波算法对于高噪声率椒盐噪声具有良好的滤波效果,还能较为有效地保留图像细节。

High-noise-ratio salt-pepper noise corrupted images filtering

A noise filtering algorithm was proposed for high-noise-ratio images corrupted by salt-pepper noise. In this algorithm, a pixel was identified as disperse noise (or edge pixel), clustered noise or no-edge pixel in an improved way based on gray absolute correlation degree. Then, disperse noise (or edge pixel) was smoothed using adaptive median filtering algorithm, which gave consideration to noise filtering and details keep togethor. And clustered noise was removed with the same value pixels within the neighbourhood area and replaced by mean value of the remainder pixels. Meanwhile, no-edge pixel was retained. Theoretical and experimental results show that the proposed algorithm performs effectivelly to high-noise-ratio salt-pepper noise, and it keeps details also.