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 nece...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.展开更多
Embedded data are used to retrieve phases quicker with high accuracy in phase-modulated holographic data storage(HDS).We propose a method to design an embedded data distribution using iterations to enhance the intensi...Embedded data are used to retrieve phases quicker with high accuracy in phase-modulated holographic data storage(HDS).We propose a method to design an embedded data distribution using iterations to enhance the intensity of the high-frequency signal in the Fourier spectrum.The proposed method increases the antinoise performance and signal-to-noise ratio(SNR)of the Fourier spectrum distribution,realizing a more efficient phase retrieval.Experiments indicate that the bit error rate(BER)of this method can be reduced by a factor of one after 10 iterations.展开更多
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)+1 种基金Natural Science Foundation of Fujian Province(2021J01160)National Natural Science Foundation of China(62061136005).
文摘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.
基金the Open Project Program of Wuhan National Laboratory for Optoelectronics(No.2019WNLOKF007)the National Key R&D Program of China(No.2018YFA0701800).
文摘Embedded data are used to retrieve phases quicker with high accuracy in phase-modulated holographic data storage(HDS).We propose a method to design an embedded data distribution using iterations to enhance the intensity of the high-frequency signal in the Fourier spectrum.The proposed method increases the antinoise performance and signal-to-noise ratio(SNR)of the Fourier spectrum distribution,realizing a more efficient phase retrieval.Experiments indicate that the bit error rate(BER)of this method can be reduced by a factor of one after 10 iterations.
