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计算成像在全息存储相位恢复中的应用研究进展

郝建颖 林雍坤 刘宏杰 陈瑞娴 宋海洋 林达奎 林枭 谭小地

数据采集与处理2024,Vol.39Issue(2):297-311,15.
数据采集与处理2024,Vol.39Issue(2):297-311,15.DOI:10.16337/j.1004-9037.2024.02.004

计算成像在全息存储相位恢复中的应用研究进展

Research Progress on Application of Computational Imaging in Holographic Storage Phase Retrieval

郝建颖 1林雍坤 2刘宏杰 2陈瑞娴 2宋海洋 2林达奎 2林枭 2谭小地2

作者信息

  • 1. 福建师范大学光电与信息工程学院,福州 350117||东京大学生产技术研究所,东京 113-8654
  • 2. 福建师范大学光电与信息工程学院,福州 350117
  • 折叠

摘要

Abstract

Holographic storage technology,as a kind of data storage technology with three-dimensional volume storage and two-dimensional data transmission,is characterized by high storage density and fast data transmission,which is one of the powerful solutions for long-term storage of massive data.The traditional holographic storage method is limited by the fact that the photodetector only responds to intensity,and is usually modulated by pure amplitude coding.However,utilizing only amplitude information cannot fully exploit the advantages of holography itself,and how to decode the phase information in a simple,fast,stable and accurate way is a real problem faced by holographic storage technology.Computational imaging opens a new way to solve phase retrieval problem for holographic storage technology because of its algorithmic versatility,high perceptual dimension characteristics and so on.This paper mainly reviews some work in recent years on solving the phase retrieval problem of holographic storage using computational imaging technology from the perspectives of iterative computational phase retrieval and deep learning phase retrieval.Analyses are conducted on the work from the perspectives of improving storage density,data reading speed,and data reading stability.Finally,we make an outlook on the future development of this direction.

关键词

全息存储/计算成像/相位恢复/迭代计算/深度学习

Key words

holographic storage/computational imaging/phase retrieval/iterative calculation/deep learning

分类

数理科学

引用本文复制引用

郝建颖,林雍坤,刘宏杰,陈瑞娴,宋海洋,林达奎,林枭,谭小地..计算成像在全息存储相位恢复中的应用研究进展[J].数据采集与处理,2024,39(2):297-311,15.

基金项目

国家重点研发计划(2018YFA0701800) (2018YFA0701800)

福建省科技重大专项(2020HZ01012) (2020HZ01012)

国家自然科学基金(U22A2080). (U22A2080)

数据采集与处理

OA北大核心CSTPCD

1004-9037

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