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A Fringe Phase Extraction Method Based on Neural Network
by
Hu, Wenxin
, Yan, Keyu
, Miao, Hong
, Fu, Yu
in
Accuracy
/ fringe pattern
/ Machine learning
/ Neural networks
/ Noise
/ phase extraction
/ U-net neural network
/ warped phase map
/ Wavelet transforms
2021
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A Fringe Phase Extraction Method Based on Neural Network
by
Hu, Wenxin
, Yan, Keyu
, Miao, Hong
, Fu, Yu
in
Accuracy
/ fringe pattern
/ Machine learning
/ Neural networks
/ Noise
/ phase extraction
/ U-net neural network
/ warped phase map
/ Wavelet transforms
2021
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Journal Article
A Fringe Phase Extraction Method Based on Neural Network
2021
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Overview
In optical metrology, the output is usually in the form of a fringe pattern, from which a phase map can be generated and phase information can be converted into the desired parameters. This paper proposes an end-to-end method of fringe phase extraction based on the neural network. This method uses the U-net neural network to directly learn the correspondence between the gray level of a fringe pattern and the wrapped phase map, which is simpler than the exist deep learning methods. The results of simulation and experimental fringe patterns verify the accuracy and the robustness of this method. While it yields the same accuracy, the proposed method features easier operation and a simpler principle than the traditional phase-shifting method and has a faster speed than wavelet transform method.
Publisher
MDPI AG,MDPI
Subject
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