基于边缘检测的高斯噪声滤波算法

Image Denoising for Gauss Noise Based on Edge Detection

针对传统去噪方法在滤除高斯噪声时导致图像边缘细节模糊的情况,提出一种基于边缘检测的去噪算法。先用Canny算子检测图像边缘,对边缘部分用K近邻平滑滤波器去噪,再对非边缘区域像素用改进的加权均值滤波器去噪。该算法具有较好的边界保持效果,与同类去噪算法相比具有更高的峰值信噪比。

In order to overcome the problem that the edge of the image is blurred when Gauss noise is eliminated by traditional denoising methods, a novel denoising algorithm based on edge detection is proposed. Firstly, the edge of the image is detected by using canny operator, then the noise in edge region is removed by using K nearest neighbor method, then the noise in the non-edge region is removed by using the improved weighted mean filter. The proposed algorithm has ideal edge preserving effect, and has a higher PSNR than other similary algorithm.