Acta Optica Sinica, Volume. 41, Issue 23, 2312001(2021)

Absolute Phase Recovery of Single Frame Composite Image Based on Convolutional Neural Network

Wenjian Li1,2, Shaoyan Gai1,2、*, Jian Yu1,2, and Feipeng Da1,2,3、**
Author Affiliations
  • 1School of Automation, Southeast University, Nanjing, Jiangsu 210096, China
  • 2Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, Jiangsu 210096, China
  • 3Shenzhen Research Institute, Southeast University, Shenzhen, Guangdong 518063, China
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    In this paper, a convolutional neural network is proposed to obtain high quality absolute phase from single frame composite images. The composite image used in the proposed method is the fringe image embedded with speckle. The convolutional neural network consists of two sub-networks, which use the fringe mode component and the speckle mode component in the composite image to solve and unfold the wrapping phase. In the process of phase unwrapping, the proposed method uses the pre-photographed composite image and its fringe order as auxiliary information to ensure the accuracy of phase unwrapping. Experimental results show that the proposed method can minimize the number of projected images by using single-frame composite images and obtain high precision absolute phase, which provides a feasible solution for 3D measurement in high precision dynamic scenes.

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    Wenjian Li, Shaoyan Gai, Jian Yu, Feipeng Da. Absolute Phase Recovery of Single Frame Composite Image Based on Convolutional Neural Network[J]. Acta Optica Sinica, 2021, 41(23): 2312001

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Apr. 14, 2021

    Accepted: Jun. 10, 2021

    Published Online: Nov. 29, 2021

    The Author Email: Gai Shaoyan (qxxymm@163.com), Da Feipeng (dafp@seu.edu.cn)

    DOI:10.3788/AOS202141.2312001

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