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Acta Optica Sinica, Volume. 37, Issue 8, 0810001(2017)

Infrared and Visible Image Fusion Based on Target Extraction and Guided Filtering Enhancement

Yiquan Wu1,2,3,4,5,6、* and Zhilai Wang1
Author Affiliations
  • 1 College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China
  • 2 Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science & Technology, Nanjing, Jiangsu 210044, China;
  • 3 Zhejiang Province Key Laboratory for Signal Processing, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
  • 4 Guangxi Key Lab of Multi-Source Information Mining and Security, Institute of Mineral Resources, Guangxi Normal University, Guilin, Guangxi 541004, China
  • 5 Key Laboratory of Geo-Spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu, Sichuan 610059, China
  • 6 Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, Ministry of Land and Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
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    [1] Wang R, Du L. Infrared and visible image fusion based on random projection and sparse representation[J]. International Journal of Remote Sensing, 35, 1640-1652(2014).

    [2] Zhao J, Gao X, Chen Y et al. Multi-window visual saliency extraction for fusion of visible and infrared images[J]. Infrared Physics & Technology, 76, 295-302(2016).

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    [4] Zhang Su, Fu Qiang, Duan Jin et al. Low contrast target polarization recognition technology based on lifting wavelet[J]. Acta Optica Sinica, 35, 0211002(2015).

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    [10] Kong W W. Technique for gray-scale visual light and infrared image fusion based on non-subsampled shearlet transform[J]. Infrared Physics & Technology, 63, 110-118(2014).

    [11] Guo Ming, Wang Shuman. Image fusion based on region and directional variance weighted entropy[J]. Systems Engineering & Electronics, 35, 720-724(2013).

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    [13] Xing Suxia, Xiao Hongbing, Chen Tianhua et al. Study of image fusion technology based on object extraction and NSCT[J]. Journal of Optoelectronics·Laser, 24, 583-588(2013).

    [14] Kong W, Lei Y, Ni X. Fusion technique for grey-scale visible light and infrared images based on non-subsampled contourlet transform and intensity-hue-saturation transform[J]. IET Signal Processing, 5, 75-80(2011).

    [15] Guo Ming, Fu Zheng, Xi Xiaoliang. Novel fusion algorithm for infrared and visible images based on local energy in NSCT domain[J]. Infrared & Laser Engineering, 41, 2229-2235(2012).

    [16] Li Jiying, Dang Jianwu, Wang Yangping. Medical image segmentation algorithm based on quantum clonal evolution and two-dimensional Tsallis entropy[J]. Journal of Computer-Aided Design & Computer Graphics, 26, 465-471(2014).

    [17] Harel J, Koch C, Perona P. Graph-based visual saliency[C]. Advances in Neural Information Processing Systems, 19, 545-552(2007).

    [18] He K, Sun J, Tang X. Guided image filtering[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 35, 1397-1409(2013).

    [19] Yin Wen, Li Yuanxiang, Zhou Zeming et al. Remote sensing image fusion method based on sparse representation[J]. Acta Optica Sinica, 33, 0428003(2013).

    CLP Journals

    [1] Zetao Jiang, Hui Wu, Xiaoling Zhou. Infrared and Visible Image Fusion Algorithm Based on Improved Guided Filtering and Dual-Channel Spiking Cortical Model[J]. Acta Optica Sinica, 2018, 38(2): 0210002

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    Yiquan Wu, Zhilai Wang. Infrared and Visible Image Fusion Based on Target Extraction and Guided Filtering Enhancement[J]. Acta Optica Sinica, 2017, 37(8): 0810001

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    Paper Information

    Category: Image Processing

    Received: Jan. 20, 2017

    Accepted: --

    Published Online: Sep. 7, 2018

    The Author Email: Wu Yiquan (nuaaimage@163.com)

    DOI:10.3788/AOS201737.0810001

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology