Journal of Atmospheric and Environmental Optics, Volume. 19, Issue 3, 381(2024)

Lightweight underwater image enhancement network based on cross-scale deep distillation feature perception

WU Xiaohua1, LI Zenglu2,3, XU Zhanghua4, and ZHOU Jingchun5、*
Author Affiliations
  • 1School of Art & Design, Sanming University, Sanming 365004, China
  • 2Network Technology Center, Sanming University, Sanming 365004, China
  • 3Fujian Provincial Key Laboratory of Resources and Environment Monitoring & Sustainable Management and Utilization,Sanming University, Sanming 365004, China
  • 4Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou 350108, China
  • 5Information Science and Technology College, Dalian Maritime University, Dalian 116026, China
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    Figures & Tables(7)
    Lightweight underwater image enhancement network structure diagram based on CSDDFP module
    Comparisons of parameter size and objective performance on LSUI400 dataset
    Visual comparisons of the mainstream methods on four benchmark datasets. (a) Input image; (b) UGAN; (c) WaterNet; (d) FUnIE_GAN; (e) UT-UIE; (f) ours; (g) ground truth
    Visual comparisons of the mainstream methods under insufficient illumination in deep water. (a) Input image; (b) UGAN; (c) WaterNet; (d) FUnIE_GAN; (e) UT-UIE; (f) ours; (g) ground truth
    Visual comparisons of the mainstream methods on texture details. (a) Input image; (b) UGAN; (c) WaterNet; (d) FUnIE_GAN; (e) UT-UIE; (f) ours; (g) ground truth
    • Table 1. Objective comparisons of different underwater image enhancement methods

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      Table 1. Objective comparisons of different underwater image enhancement methods

      MethodsLSUI400EUVP_Test515UIEB100OceanEx
      PSNRSSIMPSNRSSIMPSNRSSIMPSNRSSIM
      UWCNN17.3660.72517.7250.70414.1550.68615.9600.724
      Cycle-GAN18.3200.74917.9630.70917.7140.75821.0070.828
      SGUIE-Net19.9100.81919.1870.76021.1780.87218.6770.834
      FUnIE-GAN23.2720.81824.0770.79419.6140.81320.4480.855
      UGAN25.1170.84623.6360.80521.3680.82522.4360.822
      UT-UIE24.3490.82925.2120.81320.9160.76421.2690.822
      Ours26.6720.87225.3940.83322.7900.87722.0030.876
    • Table 2. Ablation studies of the cross-scale deep distillation feature perception module

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      Table 2. Ablation studies of the cross-scale deep distillation feature perception module

      KP/MCSDDFPSGFM[15]PPM[23]
      PSNRSSIMPSNRSSIMPSNRSSIM
      01.3425.6890.86425.6890.86425.6890.864
      12.9926.4390.87026.0120.86625.9020.865
      24.6426.6720.87226.1700.86726.0840.866
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    Xiaohua WU, Zenglu LI, Zhanghua XU, Jingchun ZHOU. Lightweight underwater image enhancement network based on cross-scale deep distillation feature perception[J]. Journal of Atmospheric and Environmental Optics, 2024, 19(3): 381

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    Paper Information

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    Received: Oct. 31, 2023

    Accepted: --

    Published Online: Jul. 17, 2024

    The Author Email: Jingchun ZHOU (zhoujingchun03@qq.com)

    DOI:10.3969/j.issn.1673-6141.2024.03.010

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