Phase retrieval from overexposed PSF: A projection-based approach

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We investigate the general adjustment of projection-based phase retrieval algorithms for use with saturated data. In the phase retrieval problem, model fidelity of experimental data containing a non-zero background level, fixed pattern noise, or overexposure, often presents a serious obstacle for standard algorithms. Recently, it was shown that overexposure can help to increase the signal-to-noise ratio in AI applications. We present our first results in exploring this direction in the phase retrieval problem, using as an example the Gerchberg-Saxton algorithm with simulated data. The proposed method can find application in microscopy, characterisation of precise optical instruments, and machine vision applications of Industry4.0.

Original languageEnglish
Title of host publicationQuantitative Phase Imaging VIII
EditorsYang Liu, Gabriel Popescu, YongKeun Park
Number of pages11
ISBN (Electronic)9781510648111
Publication statusPublished - 2022
EventQuantitative Phase Imaging VIII 2022 - Virtual, Online
Duration: 20 Feb 202224 Feb 2022

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceQuantitative Phase Imaging VIII 2022
CityVirtual, Online


  • overexposure
  • Phase retrieval
  • projection-based methods


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