A Deep Learning Approach for Digital Hologram Speckle Noise Reduction

Wen-Jing Zhou; Shili Liu; Hongbo Zhang; Yingjie Yu; Ting-Chung Poon

doi:10.1364/DH.2020.HTu5B.5

Imaging and Applied Optics Congress
OSA Technical Digest (Optica Publishing Group, 2020),
paper HTu5B.5
•https://doi.org/10.1364/DH.2020.HTu5B.5

A Deep Learning Approach for Digital Hologram Speckle Noise Reduction

Wen-Jing Zhou, Shili Liu, Hongbo Zhang, Yingjie Yu, and Ting-Chung Poon

Digital Holography and Three-Dimensional Imaging 2020

Washington, DC United States
22–26 June 2020
ISBN: 978-1-943580-77-4

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Learning-based Approaches in Digital Holography II (HTu5B)

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W. Zhou, S. Liu, H. Zhang, Y. Yu, and T. Poon, "A Deep Learning Approach for Digital Hologram Speckle Noise Reduction," in Imaging and Applied Optics Congress, OSA Technical Digest (Optica Publishing Group, 2020), paper HTu5B.5.

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Abstract

We have previously proposed spectral convolutional neural network for digital hologram speckle noise reduction. In this report, we show experimentally that it is effective for reducing multiple-levels speckle noise by using only a single hologram.

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