Temporal phase unwrapping algorithms for fringe projection profilometry: A comparative review

Zuo, Chao; Huang, Lei; Zhang, Minliang; Chen, Qian; Asundi, Anand

doi:10.1016/j.optlaseng.2016.04.022

Title: Temporal phase unwrapping algorithms for fringe projection profilometry: A comparative review

Journal Article · Fri May 06 00:00:00 EDT 2016 · Optics and Lasers in Engineering

DOI:https://doi.org/10.1016/j.optlaseng.2016.04.022· OSTI ID:1340396

Zuo, Chao ^[1]; Huang, Lei ^[2]; Zhang, Minliang ^[1]; Chen, Qian ^[3]; Asundi, Anand ^[4]

Nanjing Univ. of Science and Technology, Nanjing (China). Smart Computational Imaging Lab. (SCILab); Nanjing Univ. of Science and Technology, Nanjing (China). Jiangsu Key Lab. of Spectral Imaging & Intelligent Sense
Brookhaven National Lab. (BNL), Upton, NY (United States)
Nanjing Univ. of Science and Technology, Nanjing (China). Jiangsu Key Lab. of Spectral Imaging & Intelligent Sense
Nanyang Technological Univ., Singapore (Singapore). Centre for Optical and Laser Engineering (COLE), School of Mechanical and Aerospace Engineering

In fringe projection pro lometry (FPP), temporal phase unwrapping is an essential procedure to recover an unambiguous absolute phase even in the presence of large discontinuities or spatially isolated surfaces. So far, there are typically three groups of temporal phase unwrapping algorithms proposed in the literature: multi-frequency (hierarchical) approach, multi-wavelength (heterodyne) approach, and number-theoretical approach. In this paper, the three methods are investigated and compared in details by analytical, numerical, and experimental means. The basic principles and recent developments of the three kind of algorithms are firstly reviewed. Then, the reliability of different phase unwrapping algorithms is compared based on a rigorous stochastic noise model. Moreover, this noise model is used to predict the optimum fringe period for each unwrapping approach, which is a key factor governing the phase measurement accuracy in FPP. Simulations and experimental results verified the correctness and validity of the proposed noise model as well as the prediction scheme. The results show that the multi-frequency temporal phase unwrapping provides the best unwrapping reliability, while the multi-wavelength approach is the most susceptible to noise-induced unwrapping errors.

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Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES); National Natural Science Fund of China

Grant/Contract Number:: SC0012704; 11574152; 61505081

OSTI ID:: 1340396

Report Number(s):: BNL-112695-2016-JA

Journal Information:: Optics and Lasers in Engineering, Vol. 85, Issue C; ISSN 0143-8166

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 598 works

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Genetically encoded phase contrast agents for digital holographic microscopy Farhadi, Arash; Bedrossian, Manuel; Lee, Justin https://doi.org/10.1101/833830	posted_content	November 2019
Exhaustive dithering algorithm for 3D shape reconstruction by fringe projection profilometry Silva, Adriana; Muñoz, Antonio; Flores, Jorge L. Applied Optics, Vol. 59, Issue 13 https://doi.org/10.1364/ao.381924	journal	January 2020
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Temporal phase unwrapping using deep learning Yin, Wei; Chen, Qian; Feng, Shijie Scientific Reports, Vol. 9, Issue 1 https://doi.org/10.1038/s41598-019-56222-3	journal	December 2019
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Fringe pattern analysis using deep learning Feng, Shijie; Chen, Qian; Gu, Guohua Advanced Photonics, Vol. 1, Issue 02 https://doi.org/10.1117/1.ap.1.2.025001	journal	February 2019
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Modified Gray-Level Coding Method for Absolute Phase Retrieval Chen, Xiangcheng; Chen, Shunping; Luo, Jie Sensors, Vol. 17, Issue 10 https://doi.org/10.3390/s17102383	journal	October 2017
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Absolute Depth Measurement Using Multiphase Normalized Cross-Correlation for Precise Optical Profilometry Sensors, Vol. 19, Issue 21 https://doi.org/10.3390/s19214683	journal	October 2019
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