Lensless complex amplitude demodulation based on deep learning in holographic data storage  

作　　者：Jianying Hao Xiao Lin Yongkun Lin Mingyong Chen Ruixian Chen Guohai Situ Hideyoshi Horimai Xiaodi Tan 

机构地区：[1]College of Photonic and Electronic Engineering,Key Laboratory of Opto-Electronic Science and for Medicine of Ministry of Education,Fujian Provincial Key Laboratory of Photonics Technology,Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application,Fujian Normal University,Fuzhou 350117,China [2]Shanghai Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Shanghai 201800,China [3]HolyMine Corporation,2032-2-301 Ooka,Numazu,Shizuoka 410-0022,Japan

出　　处：《Opto-Electronic Advances》2023年第3期42-56,共15页光电进展（英文）

基　　金：We are grateful for financial supports from National Key Research and Development Program of China(2018YFA0701800);Project of Fujian Province Major Science and Technology(2020HZ01012);Natural Science Foundation of Fujian Province(2021J01160);National Natural Science Foundation of China(62061136005).

摘　　要：To increase the storage capacity in holographic data storage(HDS),the information to be stored is encoded into a complex amplitude.Fast and accurate retrieval of amplitude and phase from the reconstructed beam is necessary during data readout in HDS.In this study,we proposed a complex amplitude demodulation method based on deep learning from a single-shot diffraction intensity image and verified it by a non-interferometric lensless experiment demodulating four-level amplitude and four-level phase.By analyzing the correlation between the diffraction intensity features and the amplitude and phase encoding data pages,the inverse problem was decomposed into two backward operators denoted by two convolutional neural networks(CNNs)to demodulate amplitude and phase respectively.The experimental system is simple,stable,and robust,and it only needs a single diffraction image to realize the direct demodulation of both amplitude and phase.To our investigation,this is the first time in HDS that multilevel complex amplitude demodulation is achieved experimentally from one diffraction intensity image without iterations.

关 键 词：holographic data storage complex amplitude demodulation deep learning computational imaging 

分 类 号：TP333[自动化与计算机技术—计算机系统结构] TP391.41[自动化与计算机技术—计算机科学与技术] TP18