基于变差函数的噪声图像的多尺度边缘检测

基于区域化变量理论,针对受噪声污染的图像,本文提出了一种基于变差函数的多尺度边缘检测新方法.该方法根据图像各个不同区域的数据的不同方向的变差函数值来判断该区域是否存在边缘以及边缘的方向性,然后根据该区域边缘的方向性,在水平和垂直方向分别进行不同尺度的小波变换,进而达到在确保边缘定位准确的同时,尽最大可能去除由于噪声以及图像灰度不均匀产生的伪边缘点.仿真实验表明,本文算法在对受高斯白噪声污染较严重的图像进行边缘检测时能有效的去除噪声对图像边缘检测的影响,从而证明了该方法的可行性、有效性.

New multiscale edge detection method for noise image based on variogram function

Based on regionalized variable theory, a new multiscale edge detection method for noise image is proposed. According to the variogram values of the data in different regions with different direction, the presented method judges the existence of the edge and the direction of the edge, then in terms of the direction of the edge in the region, the wavelet transform with different scales at horizontal and vertical direction is implemented, respectively. Furthermore, to ensure the accuracy of edge location, false edge points produced by noise and uneven gray scale in image are removed as much as possible. The results of simulation indicate the proposed method can weaken the effect of the noise on edge detection, while the image is contaminated badly by Gaussian noise, thus it proves the validity and feasibility of the algorithm.Based on regionalized variable theory, a new multiscale edge detection method for noise image is proposed.