基于边缘检测的邻域加窗图像去噪算法

针对目前图像去噪算法中,消除噪声的同时又破坏边缘细节信息的问题,本文提出了结合边缘检测及邻域加窗的新算法.该算法采取平稳小波基以保持相位不变性,对低频和高频子带进行边缘检测,并将检测后的边缘信息选择后融合,即可得到原图像近似的边缘信息.依据小波方向性特点和层内相关性原理,对不同的子带在非边缘信息处采用不同的模板进行加窗处理.实验结果表明,该方法在降低了图像噪声的同时又尽可能地保留了图像的细节,较好地复原了图像.

Image De-noising Algorithm Based on Edge Detection with Neighborhood Weighed Window

An effective de-noising method in edge protecting was proposed to overcome the limitation of the current image de-nosing methods, which combines edge detection with neighborhood weighed window. This algorithm decomposes noisy images using stationary wavelet transform to keep phase invariance. Then it detects the edges of low frequency sub-band and high frequency ones, and gets the approximate information of the edge of original image by fusion the results of edge detection. Based on intra-scale dependency and directivity of wavelet coefficients, the method filters different sub-bands coefficients using corresponding forms filtering templates with weighed window, except the information of edge. A better restoration of image is demonstrated in the results of experiments, with detail of images kept as well as image noises decreasing.