Infrared and Laser Engineering, Volume. 54, Issue 8, 20250210(2025)

Infrared and visible image fusion based on cross-modal feature interaction and multi-scale reconstruction

Rui YAO*, Kai WANG, Haofan GUO, Wentao HU, and Xiangrui TIAN
Author Affiliations
  • School of Automation Enginerring, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
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    References(19)

    [7] MA J Y, ZHANG H, SHAO Z F et al. GANMcC: A generative adversarial network with multiclassification constraints for infrared and visible image fusion[J]. IEEE Transactions on Instrumentation and Measurement, 70, 1-14(2021).

    [8] LI H, WU X J. DenseFuse: A fusion approach to infrared and visible images[J]. IEEE Transactions on Image Processing, 28, 2614-2623(2018).

    [13] TANG L, YUAN J, ZHANG H et al. PIAFusion: A progressive infrared and visible image fusion network based on illumination aware[J]. Information Fusion, 83, 79-92(2022).

    [14] [14] JIA X Y, ZHU C, LI M Z, et al. LLVIP: A Visibleinfrared Paired Dataset f Lowlight Vision [C]2021 IEEECVF International Conference on Computer Vision Wkshops, 2021: 34893497.

    [15] WANG Z S, CHEN Y L, SHAO W Y et al. SwinFuse: A residual swin transformer fusion network for infrared and visible images[J]. IEEE Transactions on Instrumentation and Measurement, 71, 1-12(2022).

    [19] XIONG Z, CAO Y J, ZHANG X H et al. CMRFusion: A cross-domain multi-resolution fusion method for infrared and visible image fusion[J]. Optics and Lasers in Engineering, 170, 1-17(2023).

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    Rui YAO, Kai WANG, Haofan GUO, Wentao HU, Xiangrui TIAN. Infrared and visible image fusion based on cross-modal feature interaction and multi-scale reconstruction[J]. Infrared and Laser Engineering, 2025, 54(8): 20250210

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    Paper Information

    Category: Optical imaging, display and information processing

    Received: Apr. 3, 2025

    Accepted: --

    Published Online: Aug. 29, 2025

    The Author Email: Rui YAO (yaorui@nuaa.edu.cn)

    DOI:10.3788/IRLA20250210

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