Infrared and Laser Engineering, Volume. 51, Issue 3, 20210139(2022)

Infrared and visible image fusion of convolutional neural network and NSST

Kewei Huan, Xiangyang Li, Yutong Cao, and Xiao Chen
Author Affiliations
  • College of Physics, Changchun University of Science and Technology, Changchun 130022, China
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    References(16)

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    [4] Yuren Zhou, Anhui Geng, Qian Zhang, et al. Fusion of in-frared and visible images based on compressive sensing. Optics and Precision Engineering, 23, 855-863(2015).

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    [9] Jiao Li, Yangchun Yang, Jianwu Dang, et al. NSST and gui-ded filtering for multi-focus image fusion algorithm. Journal of Harbin Institute of Technology, 50, 145-152(2018).

    [10] M A Rahman, S Liu, C Y Wong. Multi-focal image fusion using degree of focus and fuzzy logic. Digital Signal Processing, 1, 1-19(2017).

    [11] Kangjian He, Dongming Zhou, Xuejie Zhang, et al. Multi-focus image fusion combining focus region level partition and pulsecoupled neural network. Soft Computing, 4685-4699(2019).

    [12] Hui Li, Xiaojun Wu. Infrared and visible image fusion with ResNet and zero phase component analysis. Infrared Physics and Technology, 11, 103039(2019).

    [13] Yong Yong, Zhipeng Nie, Shuying Huang, et al. Multi-level features convolutional neural network for multi-focus image fusion. IEEE Transactions on Computational Imaging, 5, 262-273(2019).

    [14] Wenbo An, Hongmei Wang. Infrared and visible image fu-sion with supervised convolutional neural network. Optik, 165120(2020).

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    [16] [16] Toet A. TNO Image fusion dataset[DBOL]. [20140426]. https:figshare.omarticlesTNImageFusionDatasetYang

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    Kewei Huan, Xiangyang Li, Yutong Cao, Xiao Chen. Infrared and visible image fusion of convolutional neural network and NSST[J]. Infrared and Laser Engineering, 2022, 51(3): 20210139

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    Paper Information

    Category: Image processing

    Received: Nov. 22, 2021

    Accepted: --

    Published Online: Apr. 8, 2022

    The Author Email:

    DOI:10.3788/IRLA20210139

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