Single-frequency and accurate phase unwrapping method using deep learning

doi:10.1016/j.optlaseng.2022.107409

	Single-frequency and accurate phase unwrapping method using deep learning
	Wang, Suqin 1; Chen, Taiqin 1; Shi, Min 1; Zhu, Dengmin 2,3; Wang, Jia 1
	2023-03-01
发表期刊	OPTICS AND LASERS IN ENGINEERING
ISSN	0143-8166
卷号	162 页码:10
摘要	Phase unwrapping is an important part of fringe projection profilometry(FPP), which greatly affects the efficiency and accuracy of reconstruction. Phase unwrapping methods with deep learning achieve single-frequency phase unwrapping without additional cameras. However, existing methods have low accuracy in the real complex scene, and can not process data whose resolution is greater than the resolution of training data. This paper introduces a neural convolutional network named as VRNet which achieves accurate and single-frequency phase unwrapping without extra cameras. VRNet with encoder-decoder structure gets multi-scale feature maps through feeding the wrapped phase map into the encoder, then fuses the feature maps recursively by using the proposed feature fusion module to accomplish precise prediction. In order to further improve the accuracy of phase unwrapping, this paper presents a phase correction method based on the distribution characteristics of the absolute phase. The method divides the cross-section of the absolute phase map into several curves and identifies a misclassified pixel by comparing its absolute phase value with the value of neighboring curves. In contrast to existing methods, the method is row-independent and does not require segmentation of image. Moreover, this paper accomplishes the prediction of high-resolution data through the phase stitching strategy and fine-tuning the phase correction method. Extensive experiments show that the proposed method is able to achieve high-accuracy and single -frequency phase unwrapping in real scenes which consist of at least one complex object, and is also effective for wrapped phase maps with a resolution larger than the training data.
关键词	Fringe projection profilometry Phase unwrapping Deep learning Semantic segmentation
DOI	10.1016/j.optlaseng.2022.107409
收录类别	SCI
语种	英语
资助项目	National Key Research and Develop-ment Program of China ; National Natural Science Foundation of China ; [2020YFB1710400] ; [61972379]
WOS研究方向	Optics
WOS类目	Optics
WOS记录号	WOS:000898786100003
出版者	ELSEVIER SCI LTD
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/20169
专题	中国科学院计算技术研究所期刊论文
通讯作者	Shi, Min
作者单位	1.North China Elect Power Univ, Sch Control & Comp Engn, 2 Beinong Rd, Beijing 102206, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 3.Chinese Acad Sci Taicang Inst Informat Technol, Taicang 215400, Peoples R China
推荐引用方式 GB/T 7714	Wang, Suqin,Chen, Taiqin,Shi, Min,et al. Single-frequency and accurate phase unwrapping method using deep learning[J]. OPTICS AND LASERS IN ENGINEERING,2023,162:10.
APA	Wang, Suqin,Chen, Taiqin,Shi, Min,Zhu, Dengmin,&Wang, Jia.(2023).Single-frequency and accurate phase unwrapping method using deep learning.OPTICS AND LASERS IN ENGINEERING,162,10.
MLA	Wang, Suqin,et al."Single-frequency and accurate phase unwrapping method using deep learning".OPTICS AND LASERS IN ENGINEERING 162(2023):10.