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

全息存储技术作为一种三维体存储、二维面数据传输的数据存储技术,具有存储密度高、数据传输快等特点,是解决海量数据长期存储的有力方案之一。传统全息存储方法受到光电探测器只对强度响应的限制,通常采用纯振幅编码进行调制,但仅利用振幅信息无法完全发挥全息技术本身优势,如何简单快速、稳定精确地解码相位信息是全息存储技术面临的现实问题。计算成像因其算法多变、高感知维度等特点为全息存储技术的相位恢复问题提供了新的思路。本文主要从迭代计算相位恢复和深度学习相位重建角度回顾近年来利用计算成像技术解决全息存储相位恢复问题的一些工作,从存储密度提升、数据读取速度提升以及数据读取稳定性等角度对工作进行了分析,并对该方向未来发展做出展望。

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.