A fractional-order optimization and parametric selection method of fractional differential masks

When processing the image, The first-order image de-fuzzification template which is defined by the traditional integer differential produces a wide edge, while the second-order template enhances texture and noise. In order to avoid the side effects of the integer differential template, this paper constructs the fractional differential mask and constructs the fractional differential mask, In the traditional fractional mask, by setting the parameters manually, the entropy of the image can be used to determine the abundance of the image information as an image test standard, and an entropy optimal fractional differential mask parameter is selected, The simulation results show that the mask can not only keep the low-frequency contour information of the smooth region, but also enhance the texture information of the high-frequency edge and high-frequency in the image. For the severe weather images, the method used in this paper has a good effect, can retain the image information very well.