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Laser & Optoelectronics Progress, Volume. 60, Issue 16, 1610013(2023)

Infrared and Visible Image Fusion with Convolutional Neural Network and Transformer

Yang Yang, Zhennan Ren*, and Beichen Li
Author Affiliations
  • School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
    Equations (18)
    References (42)
    Cited By (2)
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    Paper Information
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    Figures & Tables(10)
    Overall structure of the proposed model

    Fig. 1. Overall structure of the proposed model

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    Concrete structure of the Encoder

    Fig. 2. Concrete structure of the Encoder

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    Fusion strategy

    Fig. 3. Fusion strategy

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    Fusion results of the “Street” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

    Fig. 4. Fusion results of the “Street” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

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    Fusion results of the “Kaptein_1123” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

    Fig. 5. Fusion results of the “Kaptein_1123” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

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    Fusion results of the “Kaptein_1654” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

    Fig. 6. Fusion results of the “Kaptein_1654” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

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    Fusion results of the “Bunker” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

    Fig. 7. Fusion results of the “Bunker” image. (a) Infrared image; (b) visible image; (c) RP; (d) Wavelet; (e) ResNet-ZCA; (f) DenseFuse; (g) Dual-Branch; (h) FusionGAN; (i) GANMcC; (j) proposed method

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    Six objective metrics of different fusion models on TNO dataset. (a) En; (b) SD; (c) SF; (d) MI; (e) SCD; (f) Q_abf

    Fig. 8. Six objective metrics of different fusion models on TNO dataset. (a) En; (b) SD; (c) SF; (d) MI; (e) SCD; (f) Q_abf

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    Subjective results of the ablation experiment

    Fig. 9. Subjective results of the ablation experiment

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    • Table 1. Average value of objective results of the ablation experiment

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      Table 1. Average value of objective results of the ablation experiment

      ModelEnSDSFMISCDQ_abf
      cnn&mean6.554628.20876.02952.23801.71050.3059
      cnn+trans&mean6.657431.77636.52092.26481.72490.3110
      cnn&spa_fus6.777535.12027.46653.29541.68790.4115
      Proposed method6.963940.72717.95352.69491.76450.3695
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    Yang Yang, Zhennan Ren, Beichen Li. Infrared and Visible Image Fusion with Convolutional Neural Network and Transformer[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1610013

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    Paper Information

    Category: Image Processing

    Received: Aug. 12, 2022

    Accepted: Oct. 27, 2022

    Published Online: Aug. 18, 2023

    The Author Email: Zhennan Ren (Ren2151311@163.com)

    DOI:10.3788/LOP222265

    Topics

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