An algorithm for the estimation of point spread function based on curve edge of arbitrary shape
Zhenwei Li, CUI Guozhong, GUO Congzhou, Yang Liu · DOAJ (DOAJ: Directory of Open Access Journals) · 2019
The estimation of point spread function of remote sensing images is the necessary premise to improve the quality and to reduce the optical blur. The oblique straight edge method is greatly limited by the target. Though existing curve edge methods overcome the drawback that the oblique edge methods can only be applied to the straight edges, but will result in large estimation value error because of the stretching coordinate. An curve edge method of arbitrary shape based on the edge method of projection is proposed using the idea of moving windows. And the feasibility is explained theoretically. In the process of experimental verification, the proposed method first fits the edge points linearly, then uses the projection method to sample the gray values of the rows or columns in a selected window and aligned the sampling centers of different windows, finally estimates the point spread function using interpolation and resampling after eliminating the improper sampling points. For the edges with curvatures from 0.001 to 0.01, the peak signal-to-noise ratio can still stay above 35 dB even though under strong blur. The error of peak of the point spread function can be controlled within 20%. Compared with the traditional edge method and curve fitting method, our method has better results for all kinds of curves that the average peak signal-to-noise ratio can be improved by more than 10 dB, and has somewhat anti-noise performance.