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Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging
Phase unwrapping is a very important step in fringe projection 3D imaging. In this paper, we propose a new neural network for accurate phase unwrapping to address the special needs in fringe projection 3D imaging. Instead of labeling the wrapped phase with integers directly, a two-step training proc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374453/ https://www.ncbi.nlm.nih.gov/pubmed/32630246 http://dx.doi.org/10.3390/s20133691 |
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author | Liang, Jian Zhang, Junchao Shao, Jianbo Song, Bofan Yao, Baoli Liang, Rongguang |
author_facet | Liang, Jian Zhang, Junchao Shao, Jianbo Song, Bofan Yao, Baoli Liang, Rongguang |
author_sort | Liang, Jian |
collection | PubMed |
description | Phase unwrapping is a very important step in fringe projection 3D imaging. In this paper, we propose a new neural network for accurate phase unwrapping to address the special needs in fringe projection 3D imaging. Instead of labeling the wrapped phase with integers directly, a two-step training process with the same network configuration is proposed. In the first step, the network (network I) is trained to label only four key features in the wrapped phase. In the second step, another network with same configuration (network II) is trained to label the wrapped phase segments. The advantages are that the dimension of the wrapped phase can be much larger from that of the training data, and the phase with serious Gaussian noise can be correctly unwrapped. We demonstrate the performance and key features of the neural network trained with the simulation data for the experimental data. |
format | Online Article Text |
id | pubmed-7374453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73744532020-08-06 Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging Liang, Jian Zhang, Junchao Shao, Jianbo Song, Bofan Yao, Baoli Liang, Rongguang Sensors (Basel) Article Phase unwrapping is a very important step in fringe projection 3D imaging. In this paper, we propose a new neural network for accurate phase unwrapping to address the special needs in fringe projection 3D imaging. Instead of labeling the wrapped phase with integers directly, a two-step training process with the same network configuration is proposed. In the first step, the network (network I) is trained to label only four key features in the wrapped phase. In the second step, another network with same configuration (network II) is trained to label the wrapped phase segments. The advantages are that the dimension of the wrapped phase can be much larger from that of the training data, and the phase with serious Gaussian noise can be correctly unwrapped. We demonstrate the performance and key features of the neural network trained with the simulation data for the experimental data. MDPI 2020-07-01 /pmc/articles/PMC7374453/ /pubmed/32630246 http://dx.doi.org/10.3390/s20133691 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liang, Jian Zhang, Junchao Shao, Jianbo Song, Bofan Yao, Baoli Liang, Rongguang Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging |
title | Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging |
title_full | Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging |
title_fullStr | Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging |
title_full_unstemmed | Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging |
title_short | Deep Convolutional Neural Network Phase Unwrapping for Fringe Projection 3D Imaging |
title_sort | deep convolutional neural network phase unwrapping for fringe projection 3d imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374453/ https://www.ncbi.nlm.nih.gov/pubmed/32630246 http://dx.doi.org/10.3390/s20133691 |
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