基于深度学习的自适应光学技术研究进展及展望  

Research Progress and Prospect of Adaptive Optics Based on Deep Learning

作　　者：胡逸雯 刘鑫[1] 匡翠方[1,2] 刘旭 郝翔[1] Hu Yiwen;Liu Xin;Kuang Cuifang;Liu Xu;Hao Xiang(College of Optical Science and Engineering,Zhejiang University,Hangzhou 310027,Zhejiang,China;Research Center for Intelligent Sensing,Zhejiang Lab,Hangzhou 311100,Zhejiang,China)

机构地区：[1]浙江大学光电科学与工程学院,浙江杭州310027 [2]之江实验室智能感知研究中心,浙江杭州311100

出　　处：《中国激光》2023年第11期134-146,共13页Chinese Journal of Lasers

基　　金：国家重点研发计划(2018YFA0701400);国家自然科学基金重大研究计划培育项目(92050115);浙江省自然科学基金重点项目(LZ21F050003);浙江省科技厅浙江省“领雁”研发攻关计划(2022C01077);中央高校基本科研业务费专项资金(226-2022-00137)。

摘　　要：自适应光学是一种校正波前误差的技术,在地基望远镜、生物成像、人眼像差校正、激光通信等领域中已经有了广泛的应用。与此同时,深度学习技术的快速发展为各个领域带来了全新的方法。为了进一步提升传统自适应光学系统的性能,研究者将自适应光学技术与深度学习相结合,从实时性、抗噪声干扰能力等角度对已有自适应光学系统进行了改进。首先对目前常用的人工神经网络架构进行了介绍,然后详细阐述了近五年深度学习与自适应光学技术相结合的方法,最后对已有方法进行了总结,并对该技术未来的发展方向进行了展望。Significance Adaptive optics(AO)technology enhances imaging quality by measuring and compensating for wavefront errors.It has been widely used in ground-based telescopes,biological imaging,ocular aberration correction,and laser communication,and so on.Current AO systems can be categorized into two groups depending on the presence or absence of a wavefront sensor(WFS).Wavefront sensorless(WFSless)AO technology acquires the pupil phase via a retrieval algorithm based on the light intensity distribution.This type of technology can be divided into two kinds:single-image-based and phase-diversity-based technology.Single image-based technology measures the wavefront errors through a single intensity image.However,the phase distribution obtained from a solitary intensity image follows a one-to-many mapping relationship,resulting in limited accuracy.On the other hand,the phase-diversity-based AO technique can determine the phase distribution of the optical field on the input plane by collecting image information of the focal plane and the defocusing plane,resulting in a higher detection accuracy.However,a large number of iterations and measurements are required to obtain optimal results using traditional WFSless AO technology,making it unsuitable for high-speed and real-time scenarios.WFS AO technology employs a WFS based on the interference principle or a traditional geometric optics principle to measure the wavefront.Examples of WFSs used include phase-shifting interference WFSs,Shack-Hartmann WFSs(SHWFSs),and pyramid WFSs(PyWFSs).A high measurement accuracy is achieved using the traditional phaseshifting interference WFS method,but its real-time performance is suboptimal and is susceptible to environmental disturbances.The SHWFS is widely used in AO systems due to its simple structure and ease of operation.However,as a result of its pupil segmentation mechanism,the spatial resolution of the image is low and the dynamic range is small.While the PyWFS can detect weaker light than SHWFS AO technology,it is expensive and

关 键 词：激光光学 自适应光学 深度学习 人工神经网络 波前校正 

分 类 号：O436[机械工程—光学工程]