Phase retrieval from overexposed PSF

A projection-based approach

Conference paper (2022)

Authors

O.A. Soloviev Flexible Optical B.V., Team Michel Verhaegen - Mechanical, Maritime and Materials Engineering
J. Noom Team Michel Verhaegen - Mechanical, Maritime and Materials Engineering
Hieu Thao Nguyen Team Michel Verhaegen - Mechanical, Maritime and Materials Engineering
Gleb Vdovin Flexible Optical B.V., Team Mulders - Mechanical, Maritime and Materials Engineering
M.H.G. Verhaegen Team Michel Verhaegen - Mechanical, Maritime and Materials Engineering
Research Group
Team Michel Verhaegen (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 O.A. Soloviev, J. Noom, Hieu Thao Nguyen, Gleb Vdovin, M.H.G. Verhaegen
DOI: https://doi.org/10.1117/12.2609697
Phase retrieval Overexposure Projection-based methods
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Published Date

2022

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Michel Verhaegen

Abstract

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.

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