Advanced iterative algorithm for phase extraction: performance evaluation and enhancement

Phase-shifting techniques are extremely important in modern optical metrology. The advanced iterative algorithm (AIA) is an elegant, flexible and effective phase-shifting algorithm that can extract phase from fringe patterns with arbitrary unknown phase-shifts. However, comparing it with traditional...

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Main Authors: Chen, Yuchi, Qian, Kemao
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/161846
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1618462022-09-21T07:19:08Z Advanced iterative algorithm for phase extraction: performance evaluation and enhancement Chen, Yuchi Qian, Kemao School of Computer Science and Engineering Engineering::Computer science and engineering Interferometry Iterative Algorithm Phase-shifting techniques are extremely important in modern optical metrology. The advanced iterative algorithm (AIA) is an elegant, flexible and effective phase-shifting algorithm that can extract phase from fringe patterns with arbitrary unknown phase-shifts. However, comparing it with traditional phase-shifting algorithms, AIA has not been sufficiently investigated on (i) its applicability to different types of fringe patterns; (ii) its performance with respect to different phase-shifts, frame numbers and noise levels and thus the possibility of further improvement; and (iii) the predictability of its accuracy. To solve these problems, a series of innovations are proposed in this paper. First, condition numbers are introduced to characterize the least squares matrices used in AIA, and subsequently a fringe density requirement is suggested for the success of AIA. Second, the performance of AIA regarding different phase-shifts, frame numbers and noise levels is thoroughly evaluated by simulations, based on which, an overall phase error model is established. With such understanding, three individual improvements of AIA, i.e., controlling phase-shifts, controlling frame numbers and suppressing noise, are proposed for better performance of AIA. Third, practical methods for estimating the overall phase errors are developed to make the AIA performance predictable even before AIA is executed. We then integrate all these three innovations into an enhanced AIA (eAIA), which solves all the problems we mentioned earlier. The significant contributions of eAIA include the insurability of the convergence, the controllability of the performance, and achievability of a desired accuracy. An experiment is carried out to demonstrate the effectiveness of eAIA. Economic Development Board (EDB) Published version Economic Development Board - Singapore (S17-1579-IPP-II). 2022-09-21T06:50:51Z 2022-09-21T06:50:51Z 2019 Journal Article Chen, Y. & Qian, K. (2019). Advanced iterative algorithm for phase extraction: performance evaluation and enhancement. Optics Express, 27(26), 37634-37651. https://dx.doi.org/10.1364/OE.27.037634 1094-4087 https://hdl.handle.net/10356/161846 10.1364/OE.27.037634 31878542 2-s2.0-85077195106 26 27 37634 37651 en S17-1579-IPP-II Optics Express © 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for noncommercial purposes and appropriate attribution is maintained. All other rights are reserved. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Interferometry
Iterative Algorithm
spellingShingle Engineering::Computer science and engineering
Interferometry
Iterative Algorithm
Chen, Yuchi
Qian, Kemao
Advanced iterative algorithm for phase extraction: performance evaluation and enhancement
description Phase-shifting techniques are extremely important in modern optical metrology. The advanced iterative algorithm (AIA) is an elegant, flexible and effective phase-shifting algorithm that can extract phase from fringe patterns with arbitrary unknown phase-shifts. However, comparing it with traditional phase-shifting algorithms, AIA has not been sufficiently investigated on (i) its applicability to different types of fringe patterns; (ii) its performance with respect to different phase-shifts, frame numbers and noise levels and thus the possibility of further improvement; and (iii) the predictability of its accuracy. To solve these problems, a series of innovations are proposed in this paper. First, condition numbers are introduced to characterize the least squares matrices used in AIA, and subsequently a fringe density requirement is suggested for the success of AIA. Second, the performance of AIA regarding different phase-shifts, frame numbers and noise levels is thoroughly evaluated by simulations, based on which, an overall phase error model is established. With such understanding, three individual improvements of AIA, i.e., controlling phase-shifts, controlling frame numbers and suppressing noise, are proposed for better performance of AIA. Third, practical methods for estimating the overall phase errors are developed to make the AIA performance predictable even before AIA is executed. We then integrate all these three innovations into an enhanced AIA (eAIA), which solves all the problems we mentioned earlier. The significant contributions of eAIA include the insurability of the convergence, the controllability of the performance, and achievability of a desired accuracy. An experiment is carried out to demonstrate the effectiveness of eAIA.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Chen, Yuchi
Qian, Kemao
format Article
author Chen, Yuchi
Qian, Kemao
author_sort Chen, Yuchi
title Advanced iterative algorithm for phase extraction: performance evaluation and enhancement
title_short Advanced iterative algorithm for phase extraction: performance evaluation and enhancement
title_full Advanced iterative algorithm for phase extraction: performance evaluation and enhancement
title_fullStr Advanced iterative algorithm for phase extraction: performance evaluation and enhancement
title_full_unstemmed Advanced iterative algorithm for phase extraction: performance evaluation and enhancement
title_sort advanced iterative algorithm for phase extraction: performance evaluation and enhancement
publishDate 2022
url https://hdl.handle.net/10356/161846
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