A new wavelet transform for reliability-guided phase unwrapping of optical fringe patterns

2011 ◽  
Vol 284 (20) ◽  
pp. 4879-4883 ◽  
Author(s):  
Sikun Li ◽  
Xianyu Su ◽  
Wenjing Chen
Keyword(s):  
Wavelet Transform ◽  
Phase Unwrapping ◽  
Fringe Patterns

Multi-view phase unwrapping with composite fringe patterns

2017 ◽  
Author(s):  
Tianyang Tao ◽  
Qian Chen ◽  
Yuzhen Zhang ◽  
Yan Hu ◽  
Jian Da ◽  
...  
Keyword(s):  
Phase Unwrapping ◽  
Fringe Patterns

scholarly journals Photometric constraint for absolute phase unwrapping from single-frequency fringe patterns

2021 ◽  
Author(s):  
zhao shuai qi ◽  
Xiaojun Liu ◽  
Zhao Wang ◽  
jiaqi yang ◽  
Yanning Zhang
Keyword(s):  
Phase Unwrapping ◽  
Single Frequency ◽  
Absolute Phase ◽  
Fringe Patterns

3D shape measurement with temporal phase unwrapping and 1-D continuous wavelet transform

2021 ◽  
Author(s):  
Susana L. Burnes-Rudecino ◽  
José de Jesús Villa Hernández ◽  
Gamaliel Moreno ◽  
Ismael de la Rosa ◽  
Efrén González ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Phase Unwrapping ◽  
Shape Measurement ◽  
Continuous Wavelet ◽  
3D Shape ◽  
3D Shape Measurement ◽  
Temporal Phase

scholarly journals Temporal phase unwrapping using deep learning

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Wei Yin ◽  
Qian Chen ◽  
Shijie Feng ◽  
Tianyang Tao ◽  
Lei Huang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
High Frequency ◽  
Phase Unwrapping ◽  
Motion Artifacts ◽  
Error Sources ◽  
Actual Measurement ◽  
Temporal Phase ◽  
Fringe Patterns ◽  
Frequency Phase

AbstractThe multi-frequency temporal phase unwrapping (MF-TPU) method, as a classical phase unwrapping algorithm for fringe projection techniques, has the ability to eliminate the phase ambiguities even while measuring spatially isolated scenes or the objects with discontinuous surfaces. For the simplest and most efficient case in MF-TPU, two groups of phase-shifting fringe patterns with different frequencies are used: the high-frequency one is applied for 3D reconstruction of the tested object and the unit-frequency one is used to assist phase unwrapping for the wrapped phase with high frequency. The final measurement precision or sensitivity is determined by the number of fringes used within the high-frequency pattern, under the precondition that its absolute phase can be successfully recovered without any fringe order errors. However, due to the non-negligible noises and other error sources in actual measurement, the frequency of the high-frequency fringes is generally restricted to about 16, resulting in limited measurement accuracy. On the other hand, using additional intermediate sets of fringe patterns can unwrap the phase with higher frequency, but at the expense of a prolonged pattern sequence. With recent developments and advancements of machine learning for computer vision and computational imaging, it can be demonstrated in this work that deep learning techniques can automatically realize TPU through supervised learning, as called deep learning-based temporal phase unwrapping (DL-TPU), which can substantially improve the unwrapping reliability compared with MF-TPU even under different types of error sources, e.g., intensity noise, low fringe modulation, projector nonlinearity, and motion artifacts. Furthermore, as far as we know, our method was demonstrated experimentally that the high-frequency phase with 64 periods can be directly and reliably unwrapped from one unit-frequency phase using DL-TPU. These results highlight that challenging issues in optical metrology can be potentially overcome through machine learning, opening new avenues to design powerful and extremely accurate high-speed 3D imaging systems ubiquitous in nowadays science, industry, and multimedia.

Weighted least squares phase unwrapping based on the wavelet transform

2007 ◽  
Author(s):  
Jiafeng Chen ◽  
Haiqin Chen ◽  
Zhengang Yang ◽  
Haixia Ren
Keyword(s):  
Wavelet Transform ◽  
Least Squares ◽  
Weighted Least Squares ◽  
Phase Unwrapping

Analysis of interferometric fringe patterns by optical wavelet transform

1999 ◽  
Author(s):  
Sven Krueger ◽  
Larbi Bouamama ◽  
Hartmut Gruber ◽  
Stephan Teiwes ◽  
Guenther K. Wernicke
Keyword(s):  
Wavelet Transform ◽  
Fringe Patterns

Reliability-guided phase unwrapping in wavelet-transform profilometry

2008 ◽  
Vol 47 (18) ◽  
pp. 3369 ◽  
Author(s):  
Sikun Li ◽  
Wenjing Chen ◽  
Xianyu Su
Keyword(s):  
Wavelet Transform ◽  
Phase Unwrapping
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