Low-Photon Holographic Phase Retrieval via a Deep Decoder Neural Network

Hannah Lawrence; David A. Barmherzig; Michael Eickenberg; Marylou Gabrie; Marylou Gabrie

doi:10.1364/AIS.2021.JTu5A.19

OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES)
OSA Technical Digest (Optica Publishing Group, 2021),
paper JTu5A.19
•https://doi.org/10.1364/AIS.2021.JTu5A.19

Low-Photon Holographic Phase Retrieval via a Deep Decoder Neural Network

Hannah Lawrence, David A. Barmherzig, Michael Eickenberg, and Marylou Gabrie

Optical Sensors 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-90-3

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Joint Poster Session I (JTu5A)

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H. Lawrence, D. A. Barmherzig, M. Eickenberg, and M. Gabrie, "Low-Photon Holographic Phase Retrieval via a Deep Decoder Neural Network," in OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES), S. Buckley, F. Vanier, S. Shi, K. Walker, I. Coddington, S. Paine, K. Lok Chan, W. Moses, S. Qian, P. Pellegrino, F. Vollmer, G. , J. Jágerská, R. Menzies, L. Emmenegger, and J. Westberg, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper JTu5A.19.

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Abstract

A deep decoder neural network is applied towards the enhancement of recent algorithms for holographic Coherent Diffraction Imaging (CDI). This method does not re- quire training data, and provides improved imaging given noisy low-photon CDI data.

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