用于简单透镜成像系统的深度迭代滤波网络

Abstract

Herein, an endtoend deep neural network based on iterative adaptive filtering principle is proposed. This network aims to solve the significant image edge blurring caused by the optical structure of simple lenses. A pixel level deblurring filter is proposed, using a single glued lens with a large field of view, to effectively adapt to the spatial changes of blur and restore the blurry features of the input image. The effectiveness of the proposed method is verified through simulation and experiments conducted on a prototype camera system.