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Recovering Missing Data in Coherent Diffraction Imaging

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Abstract

A method is presented for inferring missing low-frequency data in coherent diffraction imaging via the least-squares solution of a linear system. This gives rise to improved image reconstruction when solving the phase retrieval problem.

© 2021 The Author(s)

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More Like This
Phase retrieval with data-driven dual alternating direction method of multipliers for coherent diffraction imaging

Li Song and Edmund Y. Lam
NTu1C.2 Novel Techniques in Microscopy (NTM) 2021

Deep learning approach for solving the missing cone problem in optical diffraction tomography

Joowon Lim, Ahmed B. Ayoub, and Demetri Psaltis
CF4C.5 Computational Optical Sensing and Imaging (COSI) 2020

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

Hannah Lawrence, David A. Barmherzig, Michael Eickenberg, and Marylou Gabrie
JTu5A.19 Applied Industrial Spectroscopy (AIS) 2021

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