Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-Profilometry
Eliminating the phase deviation caused by object motion plays a vital role to obtain the precise phase map to recover the object shape with phase-shifting-profilometry. Pixel-by-pixel phase retrieval using the least-squares algorithm has been widely employed to eliminate the phase deviation caused b...
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MDPI AG
2022-04-01
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Series: | Photonics |
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Online Access: | https://www.mdpi.com/2304-6732/9/5/295 |
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author | Wei Liu Xi Wang Zhipeng Chen Yi Ding Lei Lu |
author_facet | Wei Liu Xi Wang Zhipeng Chen Yi Ding Lei Lu |
author_sort | Wei Liu |
collection | DOAJ |
description | Eliminating the phase deviation caused by object motion plays a vital role to obtain the precise phase map to recover the object shape with phase-shifting-profilometry. Pixel-by-pixel phase retrieval using the least-squares algorithm has been widely employed to eliminate the phase deviation caused by moving object. However, pixel-level operation can only eliminate phase deviation within a limited range, and will bring high computational burden. In this paper, we propose an image-level phase compensation method with stochastic gradient descent (SGD) algorithm to accelerate the phase deviation elimination. Since the iteration calculation is implemented at the image-level, the proposed method can accelerate the convergence significantly. Furthermore, since the proposed algorithm is able to correct the phase deviation within <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo stretchy="false">(</mo><mo>−</mo><mi>π</mi><mo>,</mo><mi>π</mi><mo stretchy="false">)</mo></mrow></semantics></math></inline-formula>, the algorithm can tolerate a greater motion range. In addition to simulation experiments, we consider 2-D motion of the object, and conduct a series of comparative experiments to validate the effectiveness of the proposed method in a larger motion range. |
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issn | 2304-6732 |
language | English |
last_indexed | 2024-03-10T03:04:56Z |
publishDate | 2022-04-01 |
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series | Photonics |
spelling | doaj.art-ab1bcac077a24a2cacd312b561d77be52023-11-23T12:40:14ZengMDPI AGPhotonics2304-67322022-04-019529510.3390/photonics9050295Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-ProfilometryWei Liu0Xi Wang1Zhipeng Chen2Yi Ding3Lei Lu4Hubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaHubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaHubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaHubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, ChinaCollege of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, ChinaEliminating the phase deviation caused by object motion plays a vital role to obtain the precise phase map to recover the object shape with phase-shifting-profilometry. Pixel-by-pixel phase retrieval using the least-squares algorithm has been widely employed to eliminate the phase deviation caused by moving object. However, pixel-level operation can only eliminate phase deviation within a limited range, and will bring high computational burden. In this paper, we propose an image-level phase compensation method with stochastic gradient descent (SGD) algorithm to accelerate the phase deviation elimination. Since the iteration calculation is implemented at the image-level, the proposed method can accelerate the convergence significantly. Furthermore, since the proposed algorithm is able to correct the phase deviation within <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo stretchy="false">(</mo><mo>−</mo><mi>π</mi><mo>,</mo><mi>π</mi><mo stretchy="false">)</mo></mrow></semantics></math></inline-formula>, the algorithm can tolerate a greater motion range. In addition to simulation experiments, we consider 2-D motion of the object, and conduct a series of comparative experiments to validate the effectiveness of the proposed method in a larger motion range.https://www.mdpi.com/2304-6732/9/5/295phase deviation eliminationphase-shifting-profilometrythree-dimensional reconstructionsurface measurement |
spellingShingle | Wei Liu Xi Wang Zhipeng Chen Yi Ding Lei Lu Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-Profilometry Photonics phase deviation elimination phase-shifting-profilometry three-dimensional reconstruction surface measurement |
title | Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-Profilometry |
title_full | Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-Profilometry |
title_fullStr | Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-Profilometry |
title_full_unstemmed | Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-Profilometry |
title_short | Accelerated Phase Deviation Elimination for Measuring Moving Object Shape with Phase-Shifting-Profilometry |
title_sort | accelerated phase deviation elimination for measuring moving object shape with phase shifting profilometry |
topic | phase deviation elimination phase-shifting-profilometry three-dimensional reconstruction surface measurement |
url | https://www.mdpi.com/2304-6732/9/5/295 |
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