一种基于深度学习的光学合成孔径成像系统图像复原方法  

Deep Learning Based Image Restoration Method of Optical Synthetic Aperture Imaging System

作　　者：唐雎 王凯强[1,2,3] 张维 吴小龑[4] 刘国栋 邸江磊[1,2,3] 赵建林 Ju Tang;Kaiqiang Wang;Wei Zhang;Xiaoyan Wu;Guodong Liu;Jianglei Di;Jianlin Zhao(School of Physical Science and Technology,Northwestern Polytechnical University,Xi'an,Shaanxi 710129,China;Shaanxi Key Laboratory of Optical Information Technology,Xi'an,Shaanxi 710129,China;Key Laboratory of Material Physics and Chemistry Under Extraordinary Conditions,Ministry of Education,Xi'an,Shaanxi 710129,China;Institute of Fluid Physics,China Academy of Engineering Physics,Mianyang,Sichuan 621900,China)

机构地区：[1]西北工业大学物理科学与技术学院,陕西西安710129 [2]陕西省光信息技术重点实验室,陕西西安710129 [3]超常条件材料物理与化学教育部重点实验室,陕西西安710129 [4]中国工程物理研究院流体物理研究所,四川绵阳621900

出　　处：《光学学报》2020年第21期60-68,共9页Acta Optica Sinica

基　　金：国家自然科学基金(61927810,61705187);国家自然科学基金委员会与中国工程物理研究院联合基金(U1730137);陕西省自然科学基础研究计划(2018JQ6012);中央高校基本科研业务费专项资金(3102019ghxm018)。

摘　　要：光学合成孔径成像系统中光学传递函数的频率响应下降,会不可避免地导致成像模糊,因此通常需要借助维纳滤波或盲解卷积算法来实现图像复原,最终获得清晰的高分辨率图像。提出一种基于U型卷积神经网络的深度学习框架,通过MATLAB软件构建数据集,以对网络进行训练,并将所训练的U型网络与盲解卷积算法的图像复原效果进行对比。数值仿真结果表明,在弱噪声条件下,U型网络在基于光学合成孔径成像系统的图像复原中展现出较强的复原能力以及一定的泛化能力和通用性,能够实现图像的快速盲复原,因而具有潜在的应用前景。The decrease of the frequency response of the optical transfer function in the optical synthetic aperture imaging system will inevitably lead to image blur. Therefore, it is usually necessary to use the Wiener filtering or blind deconvolution algorithm to achieve image restoration, and clear and high-resolution images are obtained finally. A deep learning frame based on a U-shaped convolutional neural network is proposed. The data set is constructed by the MATLAB software to train the network. The image restoration effects of the trained U-shaped network and blind deconvolution algorithm are compared. The numerical simulation results show that the U-shaped network has strong recovery ability, generalization ability, and versatility in the image restoration based on the optical synthetic aperture imaging system under the condition of weak noise. It can realize fast blind restoration for images and has potential application prospects.

关 键 词：成像系统 光学传递函数 深度学习 卷积神经网络 光学合成孔径成像系统 

分 类 号：O436.1[机械工程—光学工程]