Breaking symmetries in data-driven phase retrieval

Raunak Manekar, Kshitij Tayal, Zhong Zhuang, Chieh Hsin Lai, Vipin Kumar, Ju Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The existing iterative and data-driven methods fail to solve phase retrieval due to the intrinsic problem symmetries. We propose two end-to-end learning methods that break the barrier and work in a new regime.

Original languageEnglish (US)
Title of host publicationComputational Optical Sensing and Imaging, COSI 2021
PublisherThe Optical Society
ISBN (Electronic)9781557528209
StatePublished - 2021
EventComputational Optical Sensing and Imaging, COSI 2021 - Part of OSA Imaging and Applied Optics Congress 2021 - Virtual, Online, United States
Duration: Jul 19 2021Jul 23 2021

Publication series

NameOptics InfoBase Conference Papers

Conference

ConferenceComputational Optical Sensing and Imaging, COSI 2021 - Part of OSA Imaging and Applied Optics Congress 2021
Country/TerritoryUnited States
CityVirtual, Online
Period7/19/217/23/21

Bibliographical note

Publisher Copyright:
© OSA 2021, © 2021 The Author(s)

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