Physics aware semi-trained deep framework for phase retrieval in digital inline holography

Ashwini S Galande; Aswathy Vijay; Hanu Phani Ram Gurram; Renu John

doi:10.1364/COSI.2023.CTu5B.4

Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP)
Technical Digest Series (Optica Publishing Group, 2023),
paper CTu5B.4
•https://doi.org/10.1364/COSI.2023.CTu5B.4

Physics aware semi-trained deep framework for phase retrieval in digital inline holography

Ashwini S Galande, Aswathy Vijay, Hanu Phani Ram Gurram, and Renu John

Computational Optical Sensing and Imaging 2023

Boston, Massachusetts United States
14–17 August 2023
ISBN: 978-1-957171-28-9

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Machine Learned Imaging II (CTu5B)

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A. S. Galande, A. Vijay, H. P. R. Gurram, and R. John, "Physics aware semi-trained deep framework for phase retrieval in digital inline holography," in Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP), Technical Digest Series (Optica Publishing Group, 2023), paper CTu5B.4.

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Abstract

We propose a hybrid deep framework that combines trained as well as untrained deep models for phase recovery in inline holography. We adopted distributed optimization which efficiently combines learned priors in loss function for high-fidelity reconstruction.

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