Acta Optica Sinica, Volume. 40, Issue 5, 0509001(2020)

Speckle Noise Reduction of Holograms Based on Spectral Convolutional Neural Network

Wenjing Zhou1、*, Shuai Zou1,2, Dengke He1, Jinglu Hu2, and Yingjie Yu1
Author Affiliations
  • 1School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
  • 2Graduate School of Information, Product and Systems, Waseda University, Kitakyushu, Fukuoka 80 80135, Japan
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    Figures & Tables(11)
    Proposed spectral convolutional neural networks architecture
    Comparison spectrogram before and after downscale. (a) Before downscale; (b) after downscale
    Noise level mapping M
    Simulated phase sample with three-peak beams. (a) Data sample 1; (b) data sample 2
    Digital holograms of two data samples from simulated phase. (a) Data sample 1; (b) data sample 2
    Simulated speckle noise holograms. (a) Data sample 1; (b) data sample 2
    Comparison of noise reduction based on different algorithms for analog noise hologram and its spectrum. (a) Original speckle noise hologram; (b) noise reduction hologram of BM3D algorithm; (c) noise reduction hologram of FFDNET network; (d) noise reduction hologram of SCNN network; (e) original speckle noise spectrogram; (f) noise reduction spectrum of BM3D algorithm; (g) noise reduction spectrum of FFDNET network; (h) noise reduction spectrum of SCNN network
    Reconstructed phase diagram and central cross section of their main peaks after noise reduction with different algorithms. (a) Reconstructed phase of original speckle noise; (b) noise reduction reconstruction phase of BM3D algorithm; (c) noise reduction reconstruction phase of FFDNET network; (d) noise reduction reconstruction phase of SCNN network; (e)--(h) are central sections along y axis of phase diagrams shown in Figs (a)--(d)
    Results of peak signal-to-noise ratio of simulated holograms with different noise reduction algorithms
    Noise and intensity reconstruction results of different algorithms for experimental hologram acquisition. (a) Reconstruction phase of original speckle noise; (b) noise reduction result of BM3D algorithm; (c) FFDNET network noise reduction; (d) SCNN network noise reduction; (e)--(h) are results of intensity reconstruction of holograms shown in Figs (a)--(d)
    Results of the peak signal-to-noise ratio of holograms collected by different noise reduction algorithms
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    Wenjing Zhou, Shuai Zou, Dengke He, Jinglu Hu, Yingjie Yu. Speckle Noise Reduction of Holograms Based on Spectral Convolutional Neural Network[J]. Acta Optica Sinica, 2020, 40(5): 0509001

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    Paper Information

    Category: Holography

    Received: Sep. 2, 2019

    Accepted: Nov. 27, 2019

    Published Online: Mar. 10, 2020

    The Author Email: Wenjing Zhou (lazybee@shu.edu.cn)

    DOI:10.3788/AOS202040.0509001

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