Acta Optica Sinica, Volume. 42, Issue 14, 1409001(2022)

Deep Learning-Based Interference-Free Hologram Generation

Jiaxue Wu1, Jinbin Gui1、*, Junchang Li1, Tai Fu1, and Wei Cheng2
Author Affiliations
  • 1Faculty of Science, Kunming University of Science and Technology, Kunming 650500, Yunnan , China
  • 2School of Information Science & Engineering, Yunnan University, Kunming 650504, Yunnan , China
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    References(30)

    [1] Gabor D. A new microscopic principle[J]. Nature, 161, 777-778(1948).

    [2] Xu F Y, Yang X, Yao J Y et al. High-resolution multiview dynamic holographic 3D display[J]. Chinese Journal of Lasers, 48, 0109001(2021).

    [3] Velez-Zea A, Torroba R. Multiplane noniterative color holographic projection[J]. Optics and Lasers in Engineering, 137, 106327(2021).

    [4] Peng Y, Nagase T, Kanamoto T et al. A virtual optical holographic encryption system using expanded Diffie-Hellman algorithm[J]. IEEE Access, 9, 22071-22077(2021).

    [5] Wang Y, Wen K, Zhang M L et al. Autofocusing techniques in digital holographic microscopy and their applications (Cover paper)(Invited)[J]. Infrared and Laser Engineering, 50, 20200530(2021).

    [6] Pu J, Gui J B, Zhang K. Multiscale digital hologram reconstruction based on deep learning[J]. Laser & Optoelectronics Progress, 59, 0209001(2022).

    [7] Yu S, Pi D P, Kang R D et al. Fast calculation method for curved computer-generated hologram based on Double-step Fresnel Diffraction[J]. Optical Technique, 47, 271-276(2021).

    [8] Goi H, Komuro K, Nomura T. Deep-learning-based binary hologram[J]. Applied Optics, 59, 7103-7108(2020).

    [9] Jiang Z X, Gui J B, Wang G Q et al. Overview of holographic-compression technology for three-dimensional display[J]. Laser & Optoelectronics Progress, 56, 240001(2019).

    [10] Liu H, Xiao Y L, Tian J L et al. Nonlinear reconstruction for off-axis Fresnel digital holography with deep learning[J]. Acta Photonica Sinica, 49, 0709001(2020).

    [11] Li J C, Fan Z B, Patrice T et al. The study of color digital holography free from the zero-order diffraction interruption[J]. Acta Physica Sinica, 60, 034204(2011).

    [12] Li J C, Song Q H, Gui J B et al. Research of image plane filtering technique in digital holographic wavefront reconstruction[J]. Acta Optica Sinica, 31, 0900135(2011).

    [13] Jiao L C, Zhang F, Liu F et al. A survey of deep learning-based object detection[J]. IEEE Access, 7, 128837-128868(2019).

    [16] Sun P Z, Zhang R F, Jiang Y et al. Sparse R-CNN: end-to-end object detection with learnable proposals[C], 14449-14458(2021).

    [17] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

    [19] Szegedy C, Vanhoucke V, Ioffe S et al. Rethinking the inception architecture for computer vision[C], 2818-2826(2016).

    [20] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

    [21] Xie S N, Girshick R, Dollár P et al. Aggregated residual transformations for deep neural networks[C], 5987-5995(2017).

    [22] Wang C Y, Liao H Y M, Wu Y H et al. CSPNet: a new backbone that can enhance learning capability of CNN[C], 1571-1580(2020).

    [24] Park D Y, Park J H. Hologram conversion for speckle free reconstruction using light field extraction and deep learning[J]. Optics Express, 28, 5393-5409(2020).

    [25] Yi F L, Moon I, Javidi B. Automated red blood cells extraction from holographic images using fully convolutional neural networks[J]. Biomedical Optics Express, 8, 4466-4479(2017).

    [26] Soukup D, Huber-Mörk R. Mobile hologram verification with deep learning[C], 169-172(2017).

    [27] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

    [28] Lecun Y, Bottou L, Bengio Y et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 86, 2278-2324(1998).

    [29] Jiao S M, Jin Z, Chang C L et al. Compression of phase-only holograms with JPEG standard and deep learning[J]. Applied Sciences, 8, 1258(2018).

    [30] Shimobaba T, Blinder D, Makowski M et al. Dynamic-range compression scheme for digital hologram using a deep neural network[J]. Optics Letters, 44, 3038-3041(2019).

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    Jiaxue Wu, Jinbin Gui, Junchang Li, Tai Fu, Wei Cheng. Deep Learning-Based Interference-Free Hologram Generation[J]. Acta Optica Sinica, 2022, 42(14): 1409001

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    Paper Information

    Category: Holography

    Received: Dec. 14, 2021

    Accepted: Feb. 21, 2022

    Published Online: Jul. 15, 2022

    The Author Email: Gui Jinbin (jinbingui@163.com)

    DOI:10.3788/AOS202242.1409001

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