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Laser & Optoelectronics Progress, Volume. 60, Issue 2, 0210011(2023)

Single Image Defogging Algorithm Based on Attention Mechanism

Ruihu Cao1, Pengchao Zhang1,2、*, Lei Wang1, Fan Zhang1, and Jie Kang1
Author Affiliations
  • 1School of Mechanical Engineering, Shaanxi University of Technology, Hanzhong 723000, Shaanxi , China
  • 2Shaanxi Key Laboratory of Industrial Automation, Hanzhong 723000, Shaanxi , China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (12)
    Equations (4)
    References (21)
    Cited By (9)
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    Figures & Tables(12)
    DRS-Dehaze Net framework

    Fig. 1. DRS-Dehaze Net framework

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    DRS-Block structure

    Fig. 2. DRS-Block structure

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    SKattention structure

    Fig. 3. SKattention structure

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    Comparison of dehazing results for synthetic foggy images. (a) Foggy images; (b) original images; (c) AOD; (d) BCCR; (e) DCP; (f) Dehazenet; (g) Yoly; (h) proposed algorithm

    Fig. 4. Comparison of dehazing results for synthetic foggy images. (a) Foggy images; (b) original images; (c) AOD; (d) BCCR; (e) DCP; (f) Dehazenet; (g) Yoly; (h) proposed algorithm

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    Result comparison for real fogged images Girls. (a) Foggy image; (b) AOD; (c) BCCR; (d) DCP; (e) Dehazenet; (f) Yoly; (g) proposed algorithm

    Fig. 5. Result comparison for real fogged images Girls. (a) Foggy image; (b) AOD; (c) BCCR; (d) DCP; (e) Dehazenet; (f) Yoly; (g) proposed algorithm

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    Result comparison for real fogged images Trees. (a) Foggy image; (b) AOD; (c) BCCR; (d) DCP; (e) Dehazenet; (f) Yoly; (g) proposed algorithm

    Fig. 6. Result comparison for real fogged images Trees. (a) Foggy image; (b) AOD; (c) BCCR; (d) DCP; (e) Dehazenet; (f) Yoly; (g) proposed algorithm

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    Result comparison for real fogged images Tian An Men. (a) Foggy image; (b) AOD; (c) BCCR; (d) DCP; (e) Dehazenet; (f) Yoly; (g) proposed algorithm

    Fig. 7. Result comparison for real fogged images Tian An Men. (a) Foggy image; (b) AOD; (c) BCCR; (d) DCP; (e) Dehazenet; (f) Yoly; (g) proposed algorithm

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    Comparison of average gradient for real fogged images

    Fig. 8. Comparison of average gradient for real fogged images

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    Comparison of information entropy for real fogged images

    Fig. 9. Comparison of information entropy for real fogged images

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    • Table 1. Experimental results for synthetic fogged images

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      Table 1. Experimental results for synthetic fogged images

      AlgorithmEvaluation indicatorConference roomRed curtainGreen tabletBedroomSitting roomAverage
      AODPSNR16.01110.54414.73415.44415.54714.456
      SSIM0.8210.6160.7970.7280.7680.746
      BCCRPSNR11.8705.07514.36516.3099.08111.340
      SSIM0.4700.2540.6780.4640.5040.474
      DCPPSNR17.24913.72119.14914.88916.89716.381
      SSIM0.7140.6340.8210.7970.6530.724
      DehazenetPSNR18.66010.51016.61617.29616.22815.862
      SSIM0.8900.6280.8640.7430.7980.785
      YolyPSNR16.46015.16116.34116.20416.33316.100
      SSIM0.6490.6760.7260.7420.5760.674
      Proposed algorithmPSNR23.36711.88819.71517.80819.55318.466
      SSIM0.8690.6250.8720.7760.8650.801

    • Table 2. Comparison of running time of different algorithms

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      Table 2. Comparison of running time of different algorithms

      ParameterDehazenetDCPMCF-DehazenetGriddehazenetProposed algorithm
      Time /s1.839.823.051.951.92

    • Table 3. Average gradient of ablation experiments

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      Table 3. Average gradient of ablation experiments

      NetworkGirlsTreesTian An Men
      DR4.5259.3093.382
      DRS5.84111.3993.789
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    Ruihu Cao, Pengchao Zhang, Lei Wang, Fan Zhang, Jie Kang. Single Image Defogging Algorithm Based on Attention Mechanism[J]. Laser & Optoelectronics Progress, 2023, 60(2): 0210011

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    Paper Information

    Category: Image Processing

    Received: Dec. 14, 2021

    Accepted: Mar. 14, 2022

    Published Online: Jan. 6, 2023

    The Author Email: Pengchao Zhang (8811202@qq.com)

    DOI:10.3788/LOP213235

    Topics

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