Infrared and visible image fusion using structure-transferring fusion method

被引:20
|
作者
Kong, Xiangyu [1 ]
Liu, Lei [1 ]
Qian, Yunsheng [1 ]
Wang, Yan [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Elect Engn & Optoelect Technol, Nanjing 210094, Jiangsu, Peoples R China
关键词
Image fusion; Infrared; Structure transfer; Night vision; MULTI-FOCUS; ALGORITHM; CURVELET; REGISTRATION;
D O I
10.1016/j.infrared.2019.03.008
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
It is commonly believed that the purpose of the image fusion is to merge as much information, such as contour, texture and intensity distribution information from original images, as possible into the fusion image. Most of the existing methods treat different source images equally with certain feature extracting operation during the fusion process. However, as for the infrared (IR) and visible image fusion problem, the features of images taken from two imaging devices with different sensitive wave bands are different, sometimes even adverse. We can't extract and preserve the opposite information at the same time. To keep the targets salient in clutter background and visual friendly, in this paper, a novel IR and visible image fusion method called structure transferring fusion method (STF) is first proposed. Firstly, the structure-transferring model is built to transfer the grayscale structure from the visible input image into the IR image. Secondly, infrared detail enhancing strategy is carried out to supplement the missing details of the IR image. Experimental results reveal that the proposed STF method is both effective and efficient for IR and visible image fusion. The final fusion image with conspicuous targets and vivid texture is conducive to night vision surveillance for human observers.
引用
收藏
页码:161 / 173
页数:13
相关论文
共 50 条
  • [21] A new color image fusion method for visible and infrared images
    Sun, Fengmei
    Li, Shutao
    Yang, Bin
    2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, VOLS 1-5, 2007, : 2043 - 2048
  • [22] The Infrared and Visible Image Fusion Method Based on Variational Multiscale
    Feng X.
    Zhang J.-H.
    Hu K.-Q.
    Zhai Z.-F.
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2018, 46 (03): : 680 - 687
  • [23] Infrared and Visible Image Fusion Method Based on Degradation Model
    Jiang Yichun
    Liu Yunqing
    Zhan Weida
    Zhu Depeng
    JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2022, 44 (12) : 4405 - 4415
  • [24] MSFNet: MultiStage Fusion Network for infrared and visible image fusion
    Wang, Chenwu
    Wu, Junsheng
    Zhu, Zhixiang
    Chen, Hao
    NEUROCOMPUTING, 2022, 507 : 26 - 39
  • [25] Infrared and visible image fusion using total variation model
    Ma, Yong
    Chen, Jun
    Chen, Chen
    Fan, Fan
    Ma, Jiayi
    NEUROCOMPUTING, 2016, 202 : 12 - 19
  • [26] Fusion of Visible and Infrared Image Using Adaptive Tetrolet Transform
    Liu, Kaifeng
    Yuan, Baohong
    Zhang, Dexiang
    Zhang, Jingjing
    PROCEEDINGS OF THE 2015 4TH INTERNATIONAL CONFERENCE ON COMPUTER, MECHATRONICS, CONTROL AND ELECTRONIC ENGINEERING (ICCMCEE 2015), 2015, 37 : 814 - 818
  • [27] Infrared and Visible Image Fusion using a Deep Learning Framework
    Li, Hui
    Wu, Xiao-Jun
    Kittler, Josef
    2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2018, : 2705 - 2710
  • [28] Infrared and Visible Image Fusion Using Anisotropic Guided Filtering
    Tong, Zhaoyang
    Yang, Shen
    Du, Shibin
    Huang, Zefeng
    LASER & OPTOELECTRONICS PROGRESS, 2024, 61 (24)
  • [29] Infrared and Visible Image Fusion Method Using Salience Detection and Convolutional Neural Network
    Wang, Zetian
    Wang, Fei
    Wu, Dan
    Gao, Guowang
    SENSORS, 2022, 22 (14)
  • [30] Infrared and Visible Image Fusion with Hybrid Image Filtering
    Zhang, Yongxin
    Li, Deguang
    Zhu, WenPeng
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020