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Single-frequency and accurate phase unwrapping method using deep learning

文献类型：期刊论文

作者Wang, Suqin3; Chen, Taiqin3; Shi, Min3; Zhu, Dengmin1,2; Wang, Jia3
刊名OPTICS AND LASERS IN ENGINEERING
出版日期2023-03-01
卷号162页码:10
关键词Fringe projection profilometry Phase unwrapping Deep learning Semantic segmentation
ISSN号0143-8166
DOI10.1016/j.optlaseng.2022.107409
英文摘要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.
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
语种英语
WOS记录号WOS:000898786100003
出版者ELSEVIER SCI LTD
源URL[http://119.78.100.204/handle/2XEOYT63/20168]  
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.Chinese Acad Sci Taicang Inst Informat Technol, Taicang 215400, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
3.North China Elect Power Univ, Sch Control & Comp Engn, 2 Beinong Rd, Beijing 102206, 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.

入库方式： OAI收割

来源：计算技术研究所

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