Image edge detection algorithm based onwavelet fractional differential theory
Zhao-Ming Wang, Jianyuan Su, Pei Zhang · 2016
In view of the traditional edge detection operator is sensitive to noise, the detection results are not satisfactory, a new edge detection method based on soft threshold wavelet de-noising and fractional differential theory is proposed in this paper. In the case of processing the image with Gauss white noise, first of all, the image is filtered by soft threshold, and then using fractional mask template. According to the classical fractional order differential G-L definition, the differential definition equation is derived, and the fractional mask operator is constructed. Compared with the traditional edge detection operator, the operator can effectively extract the edge information of the image, and have good performance of the signal to noise ratio and good positioning performance.