基于双阈值非线性导数的边缘检测算子

Edge Detection Operator Bsaed on the Dual-Threshold Nonlinear Derivative

文中提出了一种基于双阈值非线性导数算子的边缘检测方法.首先计算灰度图像的左右导数,然后通过设置双阈值对左右导数进行调整以保留有意义的边缘信息,最后合并左右导数得到图像梯度.阈值能控制平滑噪声能力,阈值能确保检测出单像素宽度的线边缘,而非线性导数计划可解决定位错位性的问题.实验结果表明,同传统的离散梯度算子相比,此算子不仅计算简单灵活,检测精度高,而且在没有平滑图像噪声的情况下得到了良好的边缘图像和信噪比.

This article presents a edge detection method,which is based on the dual-threshold nonlinear derivative operator.Firstly,gray image is used to calculate the right and left derivative.Secondly,dual-threshold is used to injust the right and left derivative to remain the meaning edge information.At last,the two derivatives are merged to get the image gradient.can control the ability of reducing noise;can ensure detection of the one pixel width edge lines;and the nonlinear derivative scheme can solve the problem of delocalization.By comparing and analying it with the traditional discrete gradient operators in the experimental demonstrations,we find that this operator is not only with advantages of sinplicity,higer accuracy of detection,but also get better edge image and higer SNR in the case of no any smootning.