为了在滤除图象椒盐噪声的同时能很好地保持图象的细节,提出了一种新颖的图象椒盐噪声非线性自适应滤除算法.该方法首先在噪声图象的滤波窗口中去除具有最大和最小灰度值的象素,然后求取剩余象素的均值,计算出该均值与对应的象素灰度值的差值,再通过与阈值相比较,确定是否用求得的均值代替原噪声图象的灰度值.阈值由图象的灰度分布自适应地确定.该算法与已发表的同类算法相比,具有更好的滤波性能,尤其在噪声严重时,其效果明显优于传统的中值滤波算法.

In order to achieve very good salt and pepper noise cancellation as well as preserving image details, a novel non-linear adaptive algorithm is proposed in this paper. The algorithm is developed by the following main steps. Firstly, pixels with maximum and minimum gray value in filtering window are excluded. Then, mean of the left pixels in filtering window is obtained. Then, difference of the mean and gray value of the corresponding pixel is calculated. Finally, the difference is compared to threshold to decide how to get gray value of output pixel, i.e., if the difference is larger than the threshold, the filtered output of the pixel is the mean, else the filtered output of the pixel is not changed. The threshold is adaptively chosen according distribution of image intensity. The results compared with other published algorithms show that the proposed algorithm can remove almost all the salt and pepper noise pixels while preserve image details very well. Even if the image is highly corrupted, it can still work properly and provide significant improvement over the conventional median filter.