为了在滤除图像椒盐噪声的同时保护图像边缘细节, 提出了一种基于连通性检测的图像椒盐噪声滤波算法。由于椒盐噪声点的灰度值与正常像素点的灰度值相比往往存在较大差异, 本算法先通过比较像素点灰度值与其邻域像素点灰度值, 将差异较大的像素点列为疑似噪声点, 然后通过检测疑似噪声点是否是图像连通区域的一部分来判断该点是否是噪声点, 最后通过中值滤波器将噪声点滤除。该算法可以有效区分图像区域边缘与椒盐噪声。实验结果表明, 该算法可以有效去除密度范围从0~0.9的椒盐噪声, 在0.9的噪声密度下, 算法的峰值信噪比仍可达到30 dB。满足有效去除不同密度范围的椒盐噪声的同时保护图像细节的要求。

In order to protect the image edge details while filtering out the image salt and pepper noise, an image salt and pepper noise filtering algorithm based on connectivity detection is proposed. Since the gray value of the salt and pepper noise point tends to be different from the gray value of the normal pixel point, the algorithm compares the pixel point gray value with the gray value of the neighborhood pixel point to make the pixel point with larger difference. It is listed as a suspected noise point, and then it is judged whether the point is a noise point by detecting whether the suspected noise point is a part of the image connected area. The noise point is finally filtered out by the median filter. The algorithm can effectively distinguish the edge of the image area from the salt and pepper noise. The experimental results show that the algorithm can effectively remove the salt and pepper noise with the density ranging from 0 to 0.9. The peak signal-to-noise ratio of the algorithm can still reach 30 dB with the noise density of 0.9. It satisfies the requirement to effectively remove the salt and pepper noise of different density ranges while protecting the image details.