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Laser & Optoelectronics Progress, Volume. 57, Issue 14, 141010(2020)

Underwater Image Restoration Based on Background Light Estimation and Transmittance Optimization

Yuzhen Liu1, Kaichen Chi1、*, and Sen Lin1,2,3
Author Affiliations
  • 1School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China
  • 2State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 3Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
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    References (20)
    Cited By (5)
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    Figures & Tables(11)
    Underwater optical imaging system

    Fig. 1. Underwater optical imaging system

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    Comparison of algorithm results. (a) Non-red channel compensation image; (b) red channel compensation image; (c) figure (a) histogram; (d) figure (b) histogram

    Fig. 2. Comparison of algorithm results. (a) Non-red channel compensation image; (b) red channel compensation image; (c) figure (a) histogram; (d) figure (b) histogram

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    Background light point extraction regions. (a) Highlight region; (b) flat region; (c) intersection region

    Fig. 3. Background light point extraction regions. (a) Highlight region; (b) flat region; (c) intersection region

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    Transmittance images. (a) Original image; (b) backscatter component transmittance; (c) R channel direct component transmittance; (d) G channel direct component transmittance; (e) B channel direct component transmittance

    Fig. 4. Transmittance images. (a) Original image; (b) backscatter component transmittance; (c) R channel direct component transmittance; (d) G channel direct component transmittance; (e) B channel direct component transmittance

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    Algorithm flow diagram

    Fig. 5. Algorithm flow diagram

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    Color recovery experiment results. (a) Original image; (b) UDCP algorithm; (c) UGAN algorithm; (d) DUIENet algorithm; (e) fusion algorithm; (f) algorithm in Ref. [7]; (g) proposed algorithm

    Fig. 6. Color recovery experiment results. (a) Original image; (b) UDCP algorithm; (c) UGAN algorithm; (d) DUIENet algorithm; (e) fusion algorithm; (f) algorithm in Ref. [7]; (g) proposed algorithm

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    Comparison of different color deviation experiments results. (a) Original image; (b) UDCP algorithm; (c) UGAN algorithm; (d) DUIENet algorithm; (e) fusion algorithm; (f) algorithm in Ref. [7]; (g) proposed algorithm

    Fig. 7. Comparison of different color deviation experiments results. (a) Original image; (b) UDCP algorithm; (c) UGAN algorithm; (d) DUIENet algorithm; (e) fusion algorithm; (f) algorithm in Ref. [7]; (g) proposed algorithm

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    Comparison of different turbidity experiment results. (a) Original image; (b) UDCP algorithm; (c) UGAN algorithm; (d) DUIENet algorithm; (e) fusion algorithm; (f) algorithm in Ref. [7]; (g) proposed algorithm

    Fig. 8. Comparison of different turbidity experiment results. (a) Original image; (b) UDCP algorithm; (c) UGAN algorithm; (d) DUIENet algorithm; (e) fusion algorithm; (f) algorithm in Ref. [7]; (g) proposed algorithm

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    Feature matching test results. (a) 1st group; (b) 2nd group; (c) 3rd group; (d) 4th group

    Fig. 9. Feature matching test results. (a) 1st group; (b) 2nd group; (c) 3rd group; (d) 4th group

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    • Table 1. Evaluation values of UCIQE index

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      Table 1. Evaluation values of UCIQE index

      No.Original imageUDCPUGANDUIENetFusionRef. [7]Proposed
      10.66560.61590.68260.65330.65300.66960.7102
      20.51130.63010.64400.52160.59060.53750.6589
      30.48930.59060.59130.48780.57130.58990.6473
      40.41980.55850.50340.51000.58260.56870.6332
      50.48590.60280.59460.48040.59850.53180.6110
      60.51940.57550.58850.50920.61930.59590.6748
      Average0.51520.59560.60070.52710.60260.58220.6559

    • Table 2. Evaluation values of NIQE index

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      Table 2. Evaluation values of NIQE index

      No.Original imageUDCPUGANDUIENetFusionRef. [7]Proposed
      13.42902.84895.40065.08633.28822.79552.6430
      22.29812.39432.14562.143513.37252.14352.1417
      33.94143.45324.91354.23193.35073.25223.2152
      43.68253.25797.544218.88193.16392.99142.9401
      53.42503.20475.70494.88253.17913.06942.9555
      63.54703.45516.41324.88283.35173.08242.7889
      Average3.38723.10245.35376.68484.95102.88912.7807
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    Yuzhen Liu, Kaichen Chi, Sen Lin. Underwater Image Restoration Based on Background Light Estimation and Transmittance Optimization[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141010

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    Paper Information

    Category: Image Processing

    Received: Oct. 12, 2019

    Accepted: Dec. 11, 2019

    Published Online: Jul. 28, 2020

    The Author Email: Kaichen Chi (1371008494@qq.com)

    DOI:10.3788/LOP57.141010

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology