图像是人类获取和交换信息的主要来源。图像的边缘是图像最基本也是最重要的特征之一。图像边缘检测是计算机视觉和图像处理领域的经典研究课题。提出由分数阶次微积分组合而成的复合导数概念,并在该复合导数的基础上提出一种边缘检测新方法。通过实验验证了新算法的有效性,展现了新算子在检测精准度与抗噪性两方面的特点。最后,对新算子与两种经典算子Canny和CRONE进行了定性和定量的分析和比较。通过比较,新算法的优越性体现在边缘定位准确,在很好地抑制虚假边缘的同时能够检测出精细的真实边缘。

Images are the main source through which humans acquire and exchange information. Edges are one of the most fundamental and important feature of image. Edge detection is a classic research problem of computer vision and image processing. In this paper we present a new edge detection operator based on a composite derivative,which is realized by the combination of fractional differentiation and integration. The features of the new operator,in terms of detection accuracy and noise immunity,are demonstrated through experiments,and the experimental results verify the effectiveness of the new operator. Finally,qualitative and quantitative comparisons of the new operator with two classical operators,Canny and CRONE,are performed. The comparisons show the superiority of the new algorithm,which is reflected in the abilities of accurate edge localization and good suppression of false edges while still being able to detect fine true edges.