Laser & Optoelectronics Progress, Volume. 59, Issue 4, 0410010(2022)

Unsupervised Infrared Image and Visible Image Fusion Algorithm Based on Deep Learning

Guoyang Chen1,2, Xiaojun Wu1,2、*, and Tianyang Xu2
Author Affiliations
  • 1School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi , Jiangsu 214122, China
  • 2Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University, Wuxi , Jiangsu 214122, China
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    References(31)

    [2] Tang C, Ling Y S, Yang H et al. Decision-level fusion tracking for infrared and visible spectra based on deep learning[J]. Laser & Optoelectronics Progress, 56, 071502(2019).

    [5] Xu L, Cui G M, Zheng C P et al. Fusion method of visible and infrared images based on multi-scale decomposition and saliency region extraction[J]. Laser & Optoelectronics Progress, 54, 111003(2017).

    [8] Zhang T F, Zhong S C, Lian C M et al. Deep learning feature fusion-based retina image classification[J]. Laser & Optoelectronics Progress, 57, 241025(2020).

    [9] Duan Z J, Li S B, Hu J J et al. Review of deep learning based object detection methods and their mainstream frameworks[J]. Laser & Optoelectronics Progress, 57, 120005(2020).

    [30] Piella G, Heijmans H. A new quality metric for image fusion[C], 111-173(2003).

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    Guoyang Chen, Xiaojun Wu, Tianyang Xu. Unsupervised Infrared Image and Visible Image Fusion Algorithm Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410010

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    Paper Information

    Category: Image Processing

    Received: Feb. 26, 2021

    Accepted: Mar. 31, 2021

    Published Online: Jan. 25, 2022

    The Author Email: Xiaojun Wu (wu_xiaojun@jiangnan.edu.cn)

    DOI:10.3788/LOP202259.0410010

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