Acta Optica Sinica, Volume. 40, Issue 21, 2111002(2020)

Algorithm for Underwater Polarization Imaging Based on Global Estimation

Fei Feng1,2, Guojun Wu1,2、*, Yafeng Wu1,2, Yuhong Miao1,2, and Bo Liu1,2
Author Affiliations
  • 1Marine Optical Technology Laboratory, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi 710119, China
  • 2Pilot National Laboratory for Marine Science and Technology, Qingdao, Shandong 266071, China
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    In order to realize the clear imaging of underwater targets with high degree of polarization (HDOP), the traditional polarization imaging model is analyzed. Based on the Schechner polarization imaging model and the definition of polarization degree, a polarization imaging restoration algorithm is proposed to globally estimate the polarization degree of backscattered light, which considers the polarization degree of reflected light of targets. The polarization imaging experiment is conducted, in which the polarization images of three kinds of targets in turbid water with different concentrations are restored. The restoration results show that the measure of enhancement value of the restored image is increased by more than 90% compared to the original Schechner algorithm. Meanwhile, the average gradient, standard deviation and information entropy of image grey are also increased. The restoration results of different polarization images of targets show that the proposed algorithm is not only suitable for the underwater targets with low degree of polarization (LDOP) and rough surfaces, but also makes the underwater targets with HDOP and smooth surfaces gain satisfactory restoration effect.

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    Fei Feng, Guojun Wu, Yafeng Wu, Yuhong Miao, Bo Liu. Algorithm for Underwater Polarization Imaging Based on Global Estimation[J]. Acta Optica Sinica, 2020, 40(21): 2111002

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    Paper Information

    Category: Imaging Systems

    Received: Jun. 8, 2020

    Accepted: Jul. 15, 2020

    Published Online: Oct. 17, 2020

    The Author Email: Wu Guojun (wuguojun@opt.ac.cn)

    DOI:10.3788/AOS202040.2111002

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