用于简单透镜成像系统的深度迭代滤波网络

Deep Iterative Filter Adaptive Network for Simple Lens Imaging System

提出一种基于迭代自适应滤波原理的端到端深度神经网络。该网络旨在解决由简单透镜的光学结构引起的显著图像边缘模糊问题。利用具有大视场的单个胶合透镜,提出一种像素级去模糊滤波器,该滤波器可有效地适应模糊的空间变化,从而恢复输入图像的模糊特征。通过模拟和在原型摄像机系统上进行的实验验证了所提方法的有效性。

Herein,an end-to-end 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.