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    Journals >Laser & Optoelectronics Progress >Volume 57 >Issue 14 >Page 141010 > Article
    • Laser & Optoelectronics Progress
    • Vol. 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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    DOI: 10.3788/LOP57.141010 Cite this Article Set citation alerts
    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 Copy Citation Text show less
    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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    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 1. Evaluation values of UCIQE 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
    Table 2. Evaluation values of NIQE index
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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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