针对受椒盐噪声不同程度污染的灰度图像滤波问题，提出了一种用于抑制椒盐噪声的自适应快速滤波算法。该算法针对像素点的不同属性采用不同策略的滤波手段，能有效保护图像细节；依据可能噪声密度自动控制滤波迭代次数，能自动抑制不同密度的椒盐噪声；基于字符串的统计排序记录方法减少了统计排序的次数，使算法一次迭代滤波耗时与标准中值滤波相当。实验结果表明，该算法自适应能力强、运算效率高、滤波效果好。

An adaptive fast filtering algorithm is proposed for the filtering problem about gray-scale image is that polluted by salt and pepper noise of different degree. This algorithm protects image details by using different filtering schemes for pixels’ different character; and controls iteration number adaptively by means of possible noise density. In this way to remove salt and pepper noise with different density. In addition, this algorithm proposes a statistical collation recording method based on string to reduce the number of statistical collation, in this way the time cost of this algorithm’s one time filtering process equals to that of the standard median filtering algorithm. The experiment shows that this algorithm has strong adaptive ability, high calculating efficiency and can achiere good filtering results.