• Journal of Atmospheric and Environmental Optics
  • Vol. 18, Issue 5, 469 (2023)
ZHANG Yimen1 and LIN Weiguo2,*
Author Affiliations
  • 1Beijing System Design Institute of Electro Mechanic Engineering, Beijing 100005, China
  • 2College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
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    DOI: 10.3969/j.issn.1673-6141.2023.05.007 Cite this Article
    Yimen ZHANG, Weiguo LIN. Infrared and visible images fusion with spatial multiscale residual networks[J]. Journal of Atmospheric and Environmental Optics, 2023, 18(5): 469 Copy Citation Text show less
    Comparison of residual network structure before and after improvement. (a) Original residual network structure;(b) improve residual network structure
    Fig. 1. Comparison of residual network structure before and after improvement. (a) Original residual network structure;(b) improve residual network structure
    Overall structure of the network
    Fig. 2. Overall structure of the network
    Spatial multi-scale attention network structure based on infrared images
    Fig. 3. Spatial multi-scale attention network structure based on infrared images
    [in Chinese]
    Fig. 4. [in Chinese]
    Loss function curve. (a) Loss of SSIM; (b) loss of MSE; (c) loss of gradient; (d) total loss
    Fig. 5. Loss function curve. (a) Loss of SSIM; (b) loss of MSE; (c) loss of gradient; (d) total loss
    IndexDenseFuseDBNFusionGANDDcGANSMSRN
    SD24.4026.3431.4745.7751.68
    AG2.973.042.675.598.24
    SSIM0.630.710.620.570.73
    EN6.346.576.647.357.69
    SCD1.331.591.161.511.76
    Time/s0.260.140.510.820.32
    Table 1. Objective evaluation results of comparative experiments
    Yimen ZHANG, Weiguo LIN. Infrared and visible images fusion with spatial multiscale residual networks[J]. Journal of Atmospheric and Environmental Optics, 2023, 18(5): 469
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