For estimating and removing the salt-and-pepper noise point accurately in image, a new adaptive median filtering algorithm was proposed. Firstly, if the pixel in the center of n x n (n is an odd integer not less than three) template was the extreme value of all the pixels in the window, it was supposed to be probably a noise point. The pixel gray value in the sequence difference between the two scripts and a template sequence of the slope of the pixel gray value within the region were used to determine the mean quasi-adaptive noise point to be the real noise points. Finally, mean filtering was done on the noised pixels. Compared with median filter, the condition of detecting noises with this method has been largely enhanced. And the method can both effectively restrain noises and maintain details.%针对图像中椒盐噪声点的准确检测与去除问题,提出一种基于斜率的自适应中值滤波算法.该算法首先用n×n(n为大于或等于3的奇数)的模板作用于待检测图像的每一个像素,若当前像素的灰度值为其邻域内所有像素灰度值的极值,判断此点为准噪声点；再利用像素灰度值序列中两段子序列斜率的差值及模板区域内像素灰度值的均值自适应地判断准噪声点是否为真正的噪声点；最后对被判定为噪声的像素做中值滤波处理.与标准中值滤波方法相比,该方法加强了噪声检测的条件.实验结果表明,该算法具有较好地去除椒盐噪声和保留细节的效果.
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