Ms. Xiaohuan Li Profile

Xiaohuan Li

at Beijing Institute of Technology

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Proceedings Article | 24 November 2021 Paper

Underwater active polarization imaging algorithm based on low-rank sparse decomposition

Xiaohuan Li, Xia Wang, Zihang Su

Proceedings Volume 12065, 120650O (2021) https://doi.org/10.1117/12.2603863

KEYWORDS: Polarization, Underwater imaging, Scattering, Light scattering, Detection and tracking algorithms, Image processing, Image quality, Submerged target modeling, Target detection, Optical imaging

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Underwater optical imaging has important application value, but it is also challenging. In traditional underwater imaging, the problems of uneven illumination, blurred texture details and low contrast often exist, in this paper we propose an underwater active polarization imaging algorithm based on low-rank sparse decomposition aiming to solve the problems above. According to the principle of underwater polarization imaging, the algorithm first performs target information enhancement on the acquired polarization images. Then combining with the low-rank characteristics of backscatter images in the scattered light field, the background information and target information could be separated from the captured images by the low-rank sparse decomposition principle, the high-quality image could be recovered from turbid water as a result. The results of experimental treatments with different turbidity levels demonstrate that the underwater polarization imaging algorithm based on low-rank sparse decomposition can improve the contrast of images, maintain the details of images and remove the background scattering at the same time. Moreover, the proposed method can effectively recover multiple targets and significantly improve the imaging quality which provides a new idea for underwater polarization clear imaging detection.

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