Volume 49 Issue 2
Mar.  2020
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Liang Tianquan, Zhang Xiaoyun, Duan Peng, Yu Huishan, Zhang Baohua, Tang Qingxin. Underwater target detection under strong scattering medium using improved dark channel method[J]. Infrared and Laser Engineering, 2020, 49(2): 0203012-0203012. doi: 10.3788/IRLA202049.0203012
Citation: Liang Tianquan, Zhang Xiaoyun, Duan Peng, Yu Huishan, Zhang Baohua, Tang Qingxin. Underwater target detection under strong scattering medium using improved dark channel method[J]. Infrared and Laser Engineering, 2020, 49(2): 0203012-0203012. doi: 10.3788/IRLA202049.0203012

Underwater target detection under strong scattering medium using improved dark channel method

doi: 10.3788/IRLA202049.0203012
  • Received Date: 2019-10-10
  • Rev Recd Date: 2019-11-15
  • Publish Date: 2020-03-02
  • For the problems of image quality degradation in underwater scene target detection, an algorithm which combined the improved dark channel with MSR was proposed, which could adaptively compute water attenuation coefficient and effectively realize the recovery of underwater target. Through the built-in underwater imaging measurement device, the detection image of the underwater simulated environment with the aid of imaging system was obtained, the underwater detection image was processed step by step according to the algorithm flow chart, and an image for the effective recovery of underwater target radiation information was obtained. In order to objectively evaluate the algorithm effect, contrast, average gradient and information entropy were adopted as quantification to evaluate indexes factors. A quantitative comparison study between this algorithm and the conventional three algorithms was performed. The result show that the improved algorithm to deal with the results is better than the selected compared algorithms under all the quantitative evaluation indexes factors. The research results provide a basic theoretical exploration method for the underwater target detection, as well as have certain guiding significance for the implementation of underwater target detection.
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    [2] William K L, Kargl S G, Thorsos E I, et al. Acoustic scattering from a solid aluminum cylinder in contact with a sand sediment:Measurements, modeling, and interpretation[J]. J Acoust Soc Am, 2010, 127(6):3356-3364.
    [3] Jaffe J S. Performance bounds on synchronous laser line scan systems[J]. Opt Express, 2005, 13(3):738-748.
    [4] Kocak D M, Dalgleish F R, Caimi F M, et al. A focus on recent developments and trends in underwater imaging[J]. Mar Technol Soc J, 2008, 42(1):52-67.
    [5] Schechner Y Y, Karpel N. Recovery of underwater visibility and structure by polarization analysis[J]. IEEE J Ocean Eng, 2005, 30(3):570-587.
    [6] Klausner N H, Azimi-Sadjadi M R. Performance prediction and estimation for underwater target detection using multichannel sonar[J]. IEEE J Ocean Eng, 2019(99):1-13.
    [7] He K M, Sun J, Tang X O. Single image haze removal using dark channel prior[J]. IEEE T Pattern Anal, 2011, 33(12):2341-2353.
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Underwater target detection under strong scattering medium using improved dark channel method

doi: 10.3788/IRLA202049.0203012
  • 1. School of Environment and Planning, Liaocheng University, Liaocheng 252059, China;
  • 2. School of Physics Science and Information Technology, Liaocheng University, Liaocheng 252059, China;
  • 3. School of Computer, Liaocheng University, Liaocheng 252059, China

Abstract: For the problems of image quality degradation in underwater scene target detection, an algorithm which combined the improved dark channel with MSR was proposed, which could adaptively compute water attenuation coefficient and effectively realize the recovery of underwater target. Through the built-in underwater imaging measurement device, the detection image of the underwater simulated environment with the aid of imaging system was obtained, the underwater detection image was processed step by step according to the algorithm flow chart, and an image for the effective recovery of underwater target radiation information was obtained. In order to objectively evaluate the algorithm effect, contrast, average gradient and information entropy were adopted as quantification to evaluate indexes factors. A quantitative comparison study between this algorithm and the conventional three algorithms was performed. The result show that the improved algorithm to deal with the results is better than the selected compared algorithms under all the quantitative evaluation indexes factors. The research results provide a basic theoretical exploration method for the underwater target detection, as well as have certain guiding significance for the implementation of underwater target detection.

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