Acta Optica Sinica, Volume. 42, Issue 9, 0911001(2022)

Terahertz Light Field Imaging Occlusion Removing Algorithm Based on Multi-Perspective Synthetic Aperture

Moxuan Yang1,2,3,4, Yuanmeng Zhao1,2,3,4、*, Fengxia Zhu1,2,3,4, Hongfei Zhang1,2,3,4, Zhilong Li1,2,3,4, and Cunlin Zhang1,2,3,4
Author Affiliations
  • 1Key Laboratory of Terahertz Optoelectronics, Ministry of Education, Beijing 100048, China
  • 2Beijing Key Laboratory for Terahertz Spectroscopy and Imaging, Beijing 100048, China
  • 3Beijing Advanced Innovation Center for Imaging Theory and Technology, Beijing 100048, China
  • 4Department of Physics, Capital Normal University, Beijing 100048, China
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    In order to solve the problem that the acquisition of interesting information is affected by foreground occlusion in terahertz field imaging, a terahertz light field imaging occlusion culling algorithm based on multi-perspective synthetic aperture is proposed. Based on the analysis of digital refocusing principle of terahertz light field imaging, the original data of the terahertz light field is collected by using a terahertz focal plane array camera, and the depth of digital refocusing is located by determining the minimum generalization error. Finally, the reconstructed image is enhanced by using empirical mode decomposition (EMD) method. The terahertz image of the object with clear contour and interference suppression is obtained. The experimental results show that the combination of terahertz light field technology and synthetic aperture technology can effectively reduce the influence of occlusion, and it is proved that EMD method has the ability to improve the quality of terahertz image.

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    Moxuan Yang, Yuanmeng Zhao, Fengxia Zhu, Hongfei Zhang, Zhilong Li, Cunlin Zhang. Terahertz Light Field Imaging Occlusion Removing Algorithm Based on Multi-Perspective Synthetic Aperture[J]. Acta Optica Sinica, 2022, 42(9): 0911001

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    Paper Information

    Category: Imaging Systems

    Received: Sep. 29, 2021

    Accepted: Nov. 15, 2021

    Published Online: May. 6, 2022

    The Author Email: Zhao Yuanmeng (zhao.yuanmeng@cnu.edu.cn)

    DOI:10.3788/AOS202242.0911001

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