Advanced Photonics, Volume. 1, Issue 1, 016004(2019)

End-to-end deep learning framework for digital holographic reconstruction

Zhenbo Ren1,2, Zhimin Xu3, and Edmund Y. Lam1、*
Author Affiliations
  • 1University of Hong Kong, Department of Electrical and Electronic Engineering, Pokfulam, Hong Kong, China
  • 2Northwestern Polytechnical University, School of Natural and Applied Sciences, Xi’an, China
  • 3SharpSight Limited, Hong Kong, China
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    References(46)

    [2] U. Schnars et al. Digital Holography and Wavefront Sensing(2015).

    [8] M. Born, E. Wolf. Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light(1999).

    [10] J. W. Goodman. Introduction to Fourier Optics(2017).

    [21] D. C. Ghiglia, M. D. Pritt. Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software, 4(1998).

    [40] I. Goodfellow, Y. Bengio, A. Courville. Deep Learning(2016).

    CLP Journals

    [1] Hang LIU, Yong-liang XIAO, Jun-long TIAN, Hong-xing LI, Jian-xin ZHONG. Nonlinear Reconstruction for Off-axis Fresnel Digital Holography with Deep Learning[J]. Acta Photonica Sinica, 2020, 49(7): 709001

    [2] Shuo Zhu, Enlai Guo, Jie Gu, Lianfa Bai, Jing Han, "Imaging through unknown scattering media based on physics-informed learning," Photonics Res. 9, B210 (2021)

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    Zhenbo Ren, Zhimin Xu, Edmund Y. Lam, "End-to-end deep learning framework for digital holographic reconstruction," Adv. Photon. 1, 016004 (2019)

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    Paper Information

    Category: Research Articles

    Received: Jun. 6, 2018

    Accepted: Nov. 14, 2018

    Published Online: Feb. 18, 2019

    The Author Email: Lam Edmund Y. (elam@eee.hku.hk)

    DOI:10.1117/1.AP.1.1.016004

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