Deep learning-based holographic reconstruction in digital holography

Jianglei Di; Kaiqiang Wang; Ying Li; Jianlin Zhao

doi:10.1364/DH.2020.HTu4B.2

Imaging and Applied Optics Congress
The Optical Society (Optica Publishing Group, 2020),
paper HTu4B.2
•https://doi.org/10.1364/DH.2020.HTu4B.2

Deep learning-based holographic reconstruction in digital holography

Jianglei Di, Kaiqiang Wang, Ying Li, and Jianlin Zhao

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 I (HTu4B)

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J. Di, K. Wang, Y. Li, and J. Zhao, "Deep learning-based holographic reconstruction in digital holography," in Imaging and Applied Optics Congress, The Optical Society (Optica Publishing Group, 2020), paper HTu4B.2.

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Abstract

We propose a one-to-two neural network framework for digital holographic reconstruction from a single-wavelength or dual-wavelength digital hologram and also propose a one to one neural network to achieve phase unwrapping.

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