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Laser & Optoelectronics Progress, Volume. 62, Issue 8, 0837004(2025)

Image Dehazing Algorithm Based on Multi-Dimensional Attention Feature Fusion

Xuguang Zhu* and Nan Jiang
Author Affiliations
  • College of Software, Liaoning Technical University, Huludao 125105, Liaoning , China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (14)
    Equations (14)
    References (30)
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    Figures & Tables(14)
    Overall architecture of MAFF-Net

    Fig. 1. Overall architecture of MAFF-Net

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    Structure of channel attention module

    Fig. 2. Structure of channel attention module

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    Structure of spatial attention module

    Fig. 3. Structure of spatial attention module

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    Structure of pixel attention module

    Fig. 4. Structure of pixel attention module

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    Structure of MPFF module

    Fig. 5. Structure of MPFF module

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    Structure of Bi-GFF module

    Fig. 6. Structure of Bi-GFF module

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    Partial experimental results of different algorithms on RESIDE SOTS Indoor dataset. (a) Hazy images; (b) DCP; (c) DehazeNet; (d) GFN; (e) AOD-Net; (f) GCA-Net; (g) DCPDN; (h) MsCNN; (i) proposed algorithm; (j) standard fog free images

    Fig. 7. Partial experimental results of different algorithms on RESIDE SOTS Indoor dataset. (a) Hazy images; (b) DCP; (c) DehazeNet; (d) GFN; (e) AOD-Net; (f) GCA-Net; (g) DCPDN; (h) MsCNN; (i) proposed algorithm; (j) standard fog free images

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    Partial experimental results of different algorithms on RESIDE SOTS Outdoor dataset. (a) Hazy images; (b) DCP; (c) DehazeNet; (d) GFN; (e) AOD-Net; (f) GCA-Net; (g) DCPDN; (h) MsCNN; (i) proposed algorithm; (j) standard fog free images

    Fig. 8. Partial experimental results of different algorithms on RESIDE SOTS Outdoor dataset. (a) Hazy images; (b) DCP; (c) DehazeNet; (d) GFN; (e) AOD-Net; (f) GCA-Net; (g) DCPDN; (h) MsCNN; (i) proposed algorithm; (j) standard fog free images

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    Partial experimental results of different aogorithms on I-Hazy and O-Hazy datasets. (a) Hazy images; (b) DCP; (c) DehazeNet; (d) GFN; (e) AOD-Net; (f) GCA-Net; (g) DCPDN; (h) MsCNN; (i) proposed algorithm; (j) standard fog free images

    Fig. 9. Partial experimental results of different aogorithms on I-Hazy and O-Hazy datasets. (a) Hazy images; (b) DCP; (c) DehazeNet; (d) GFN; (e) AOD-Net; (f) GCA-Net; (g) DCPDN; (h) MsCNN; (i) proposed algorithm; (j) standard fog free images

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    Dehazing effects of different loss functions. (a) Hazy image; (b) L1SSIM; (c) perceived loss; (d) LMS-SSIM; (e) L1SSIM+perceived loss; (f) perceived loss+LMS-SSIM; (g) L1SSIM+LMS-SSIM; (h) L1SSIM+perceived loss+LMS-SSIM; (i) proposed algorithm

    Fig. 10. Dehazing effects of different loss functions. (a) Hazy image; (b) L1SSIM; (c) perceived loss; (d) LMS-SSIM; (e) L1SSIM+perceived loss; (f) perceived loss+LMS-SSIM; (g) L1SSIM+LMS-SSIM; (h) L1SSIM+perceived loss+LMS-SSIM; (i) proposed algorithm

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    Dehazing effects of different modules. (a) Hazy image; (b) SUAM; (c) MPFF; (d) SUAM+MPFF; (e) SUAM+MPFF+Bi-GFF

    Fig. 11. Dehazing effects of different modules. (a) Hazy image; (b) SUAM; (c) MPFF; (d) SUAM+MPFF; (e) SUAM+MPFF+Bi-GFF

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    • Table 1. PSNR and SSIM of different dehazing algorithms on different datasets

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      Table 1. PSNR and SSIM of different dehazing algorithms on different datasets

      AlgorithmPSNR /dBSSIM
      RESIDE SOTS IndoorRESIDE SOTS OutdoorI-HAZYO-HAZYRESIDE SOTS IndoorRESIDE SOTS OutdoorI-HAZYO-HAZY
      DCP17.3615.2113.8614.250.80110.79680.56800.6496
      DehazeNet22.2319.8313.4813.640.84620.81260.53080.6136
      GFN22.7819.7216.3317.740.85350.83690.72350.7663
      AOD-Net20.2818.5715.3515.450.80270.78730.62330.5849
      GCA-Net30.0327.6318.1720.900.95560.93790.78580.8036
      DCPDN15.8214.7713.3814.600.79180.78320.53550.6323
      MsCNN22.8019.7216.7815.870.90710.83680.65600.5002
      Proposed32.8030.5721.7325.270.96020.94410.82710.8419

    • Table 2. Ablation experimental results of different loss functions

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      Table 2. Ablation experimental results of different loss functions

      Loss functionPSNR /dBSSIM
      L1SSIM24.360.8339
      Perceived loss23.100.8153
      LMS-SSIM24.700.8330
      L1SSIM+perceived loss24.380.8356
      Perceived loss+LMS-SSIM23.890.8250
      L1SSIM+ LMS-SSIM24.470.8362
      L1SSIM+perceived loss+LMS-SSIM25.270.8419

    • Table 3. Ablation experimental results of different modules

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      Table 3. Ablation experimental results of different modules

      ModulePSNR /dBSSIMAverage time /s
      SUAM23.920.83170.31
      MPFF24.190.82530.24
      SUAM+MPFF24.660.83550.26
      SUAM+MPFF+Bi-GFF25.270.84190.28
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    Xuguang Zhu, Nan Jiang. Image Dehazing Algorithm Based on Multi-Dimensional Attention Feature Fusion[J]. Laser & Optoelectronics Progress, 2025, 62(8): 0837004

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    Paper Information

    Category: Digital Image Processing

    Received: Aug. 6, 2024

    Accepted: Oct. 8, 2024

    Published Online: Mar. 25, 2025

    The Author Email:

    DOI:10.3788/LOP241813

    CSTR:32186.14.LOP241813

    Topics

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