一种消除高密度椒盐噪声的迭代中值滤波算法

针对现有滤波方法处理高密度椒盐噪声的不足，提出一种简单有效的迭代中值滤波算法。该方法首先依据像素的强度值判断噪声点的位置，然后在循环迭代的处理框架内，对噪声像元进行逐步恢复。若噪声影像中包含足够的健康信息，则利用局部灰度差异控制项，完成对滤波结果的进一步优化。基于标准测试影像的实验表明，该方法能更为精确地恢复出被椒盐噪声污染的影像细节信息，其处理结果在目视及定量评价上均优于4种对比的滤波方法；且该方法的处理优势在影像椒盐噪声比例高达95%的情况下也依旧显著。

A Novel Median Filter to Iteratively Remove Salt-and-Pepper Noise from Highly Corrupted Images

In this paper, we propose a simple but efficient filter to effectively remove salt-and-pepper noise from highly corrupted images inspired by the corresponding limitations of existing filtering methods. After ensuring the location of ill pixels based on their intensity value, our method then utilizes the iterative processing framework to gradually restore the noisy images. When the useful information of one corrupted image is much enough, the proposed method can refine the results through particular designed criterion. The experiments from standard test images show that the proposed method can better recover the detail information and maintain the optimal performances qualitatively and quantitatively in the comparisons. Even the ratio of salt-and-pepper noise is as high as 95%, the advantage of our filter is still significant.