基于多尺度自适应扩散方程的边缘检测方法

针对Canny算法对较高密度椒盐噪声和双阈值选取方面存在的不足，提出一种改进方法，采用多尺度自适应各向异性扩散方程对图像进行平滑，有效去除较高密度脉冲信号的同时又可以更好地保留边缘轮廓信息。在双阈值门限的选取上采用最大类间方差法根据图像的灰度信息自适应地选取，可以更好地满足实时性要求。为验证其性能，在不同噪声浓度情况下进行实验，结果表明，改进的边缘检测算法可以更完整地保留边缘信息，提高边缘检测的准确性，得到较理想的边缘轮廓信息。

An edge detection algorithm based onmulti-scale adaptive diffusion equations

Aiming at the shortcomings of Canny's algorithm in the selection of high-density salt-pepper noise and double threshold, an improved method is proposed, in which multi-scale adaptive anisotropic diffusion equations are used to smooth images in order to effectively remove the high-density pulse signal and better retain edge profile information. In the selection of double threshold, the OTSU method is used to select an adaptive threshold according to the gray information of images, which can better meet the real-time requirements. To verify the algorithm's performance, experiments were carried out under different noise concentrations. Experimental results show that the improved edge detection algorithm can keep a complete set of edges, improve the accuracy of edge detection and get ideal edge profile information.