Deep Phase Retrieval by a Learnable Filtered Spectral Initialization

David Morales; Andrés Jerez; Henry Arguello

doi:10.1364/COSI.2021.CTh4A.6

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper CTh4A.6
•https://doi.org/10.1364/COSI.2021.CTh4A.6

Deep Phase Retrieval by a Learnable Filtered Spectral Initialization

David Morales, Andrés Jerez, and Henry Arguello

Computational Optical Sensing and Imaging 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-89-7

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Phase Retrieval (CTh4A)

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D. Morales, A. Jerez, and H. Arguello, "Deep Phase Retrieval by a Learnable Filtered Spectral Initialization," in OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), H. Hua, B. Javidi, M. Martinez-Corral, O. Matoba, A. Stern, S. Thibault, T. Alieva, J. Ke, F. Willomitzer, F. Okten, P. Silveira, P. Banerjee, E. Stoykova, D. Chu, J. Park, F. Imai, C. Joo, M. Digman, D. Gardner, S. Gladysz, D. LeMaster, S. Basu, and O. Korotkova, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper CTh4A.6.

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Abstract

This work proposes a deep neural network approach for the phase retrieval problem, which learns a filtered spectral initialization. Simulation results show that the proposed approach requires fewer snapshots and power iterations than state-of-the-art.

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