滤除图象噪声时，虽然利用的先验知识越多，其滤波效果越好，但是一般情况下，由于只能得到一幅被污染的图象，无法获得这些先验知识，因而滤波效果较差。为了解决该问题，提出了一种去除图象中椒盐噪声的新型滤波器。该滤波器首先给出了一种有效的估计原图象直方图的方法，进而利用估计直方图的信息来进行滤波；然后对滤波窗口中的像素进行一种排除最大和最小灰度值的操作，以滤除椒盐噪声点。实验表明，该方法滤波效果优于传统的滤波器和其他模糊滤波器，特别是当噪声概率超过0．3时，这种优势尤为明显。

The more priori knowledge used in removing image noise, the better will the effect of removing image noise be, but we can only get a noise corrupted image in general condition, and can't get this priori knowledge, so effect of removing image noise is not good. A novel filter for removing salt & pepper noise of image is proposed in this paper for solving this problem. Firstly, the filter provides an effective approach for estimating histogram of original image, then gets a membership function through the histogram, and then establishes a weighted fuzzy mean filter based on this membership function, so the filter utilizes the information of the estimated histogram to remove salt and pepper noise; Secondly, the filter does an operation of excluding maximum and minimum gray intensity to the pixels of filter windows in order to remove salt and pepper noise points. Experimental results show that the filter gives superior performance compared with conventional filters and other fuzzy filter, especially, the superiority will more obvious when noise probability exceeds 0 3.