Literature DB >> 30732380

Polarization-based exploration for clear underwater vision in natural illumination.

Fei Liu, Yi Wei, Pingli Han, Kui Yang, Lu Bai, Xiaoepeng Shao.   

Abstract

Underwater imaging provides human vision system friendly images; however, it often suffers from severe image degradation. This research developed an underwater polarization imaging model, which considers the water scattering effect, as well as absorption effect. It fully explored the polarization information of the target scene that backscattered light is partially polarized and target light is unpolarized. Then backscattered light is first estimated and removed. The target scene's distance information is derived based upon the polarization information, and then applied to develop a distance-based Lambertian model. This model enables estimation of the intensity loss caused by water absorption and accurate target radiance recovery. Furthermore, real-world experiments show that the developed model handled the underwater image degradation well. In particular, it enables effective color cast correction resulting from water absorption, which traditional imaging methods always ignore.

Entities:  

Year:  2019        PMID: 30732380     DOI: 10.1364/OE.27.003629

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  2 in total

1.  Underwater Object Detection and Reconstruction Based on Active Single-Pixel Imaging and Super-Resolution Convolutional Neural Network.

Authors:  Mengdi Li; Anumol Mathai; Stephen L H Lau; Jian Wei Yam; Xiping Xu; Xin Wang
Journal:  Sensors (Basel)       Date:  2021-01-05       Impact factor: 3.576

2.  Deblurring Ghost Imaging Reconstruction Based on Underwater Dataset Generated by Few-Shot Learning.

Authors:  Xu Yang; Zhongyang Yu; Pengfei Jiang; Lu Xu; Jiemin Hu; Long Wu; Bo Zou; Yong Zhang; Jianlong Zhang
Journal:  Sensors (Basel)       Date:  2022-08-17       Impact factor: 3.847

  2 in total

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