Evaluation of pixel-wise geometric constraint-based phase-unwrapping method for low signal-to-noise-ratio (SNR) phase

Yatong An; Ziping Liu; Song Zhang

doi:10.1515/aot-2016-0048

Article

Evaluation of pixel-wise geometric constraint-based phase-unwrapping method for low signal-to-noise-ratio (SNR) phase

Yatong An
Yatong An is currently a PhD student in the School of Mechanical Engineering at Purdue University. He received his MPhil degree in Computer Science from the University of Hong Kong in August 2015. In 2013, he received his BS degree from the Department of Control Science and Engineering in Zhejiang University, China. His research interests include optical measurement, 3D reconstruction, computer vision, control, robotics, and machine learning.
, Ziping Liu
Ziping Liu is an undergraduate student in the School of Mechanical Engineering at Purdue University. He is currently working with Dr. Zhang as an undergraduate research assistant in the XYZT Lab. His research interests include high-speed 3D optical metrology and computational imaging.
and Song Zhang
Song Zhang is an associate professor of Mechanical Engineering at Purdue University. He received his PhD degree in Mechanical Engineering from Stony Brook University in 2005. He was a postdoctoral fellow at Harvard University for 3 years and joined Iowa State University as an assistant in 2008 before moving to Purdue in 2015. He won the AIAA Best Paper Award, Best of SIGGRAPH by the Walt Disney, NSF CAREER award, Stony Brook University’s “40 under 40 Alumni Award”, and Discovery in Mechanical Engineering Award. He is a fellow of SPIE-the International Society for Optics and Photonics, and a senior member of Optical Society of America (OSA). His current research focuses on developing superfast, super-resolution 3-D imaging technologies and on exploring their applications.

Published/Copyright: December 15, 2016

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From the journal Advanced Optical Technologies Volume 5 Issue 5-6

Abstract

This paper evaluates the robustness of our recently proposed geometric constraint-based phase-unwrapping method to unwrap a low-signal-to-noise ratio (SNR) phase. Instead of capturing additional images for absolute phase unwrapping, the new phase-unwrapping algorithm uses geometric constraints of the digital fringe projection (DFP) system to create a virtual reference phase map to unwrap the phase pixel by pixel. Both simulation and experimental results demonstrate that this new phase-unwrapping method can even successfully unwrap low-SNR phase maps that bring difficulties for conventional multi-frequency phase-unwrapping methods.

Keywords: 3D shape measurement; noise; phase retrieval; phase unwrapping

About the authors

Yatong An

Yatong An is currently a PhD student in the School of Mechanical Engineering at Purdue University. He received his MPhil degree in Computer Science from the University of Hong Kong in August 2015. In 2013, he received his BS degree from the Department of Control Science and Engineering in Zhejiang University, China. His research interests include optical measurement, 3D reconstruction, computer vision, control, robotics, and machine learning.

Ziping Liu

Ziping Liu is an undergraduate student in the School of Mechanical Engineering at Purdue University. He is currently working with Dr. Zhang as an undergraduate research assistant in the XYZT Lab. His research interests include high-speed 3D optical metrology and computational imaging.

Song Zhang

Song Zhang is an associate professor of Mechanical Engineering at Purdue University. He received his PhD degree in Mechanical Engineering from Stony Brook University in 2005. He was a postdoctoral fellow at Harvard University for 3 years and joined Iowa State University as an assistant in 2008 before moving to Purdue in 2015. He won the AIAA Best Paper Award, Best of SIGGRAPH by the Walt Disney, NSF CAREER award, Stony Brook University’s “40 under 40 Alumni Award”, and Discovery in Mechanical Engineering Award. He is a fellow of SPIE-the International Society for Optics and Photonics, and a senior member of Optical Society of America (OSA). His current research focuses on developing superfast, super-resolution 3-D imaging technologies and on exploring their applications.

Acknowledgment

This study was sponsored by the National Science Foundation (NSF) under grant numbers CMMI-1521048. The views expressed in this paper are those of the authors and not necessarily those of the NSF.

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Received: 2016-8-31

Accepted: 2016-11-8

Published Online: 2016-12-15

Published in Print: 2016-12-1

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Articles in the same Issue

https://doi.org/10.1515/aot-2016-0048

Keywords for this article

3D shape measurement; noise; phase retrieval; phase unwrapping