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Volume 45 Issue 8
Aug.  2023
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GONG Jiamin, WU Yijie, LIU Fang, ZHANG Yunsheng, LEI Shutao, ZHU Zehao. Image Fusion Algorithm Based on Improved Fuzzy C-means Clustering[J]. Infrared Technology , 2023, 45(8): 849-857.
Citation: GONG Jiamin, WU Yijie, LIU Fang, ZHANG Yunsheng, LEI Shutao, ZHU Zehao. Image Fusion Algorithm Based on Improved Fuzzy C-means Clustering[J]. Infrared Technology , 2023, 45(8): 849-857.
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Image Fusion Algorithm Based on Improved Fuzzy C-means Clustering

  • Xi 'an University of Posts and Telecommunications School of Communication and Information Engineering, Xi 'an 710061, China

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  • Received Date: June 12, 2021
  • Revised Date: August 17, 2021
    Graphical Abstract
    • Abstract
  • To obtain more prominent target information and retain more textural details in infrared and visible light fusion images, an infrared and visible light image fusion algorithm based on the non-subsample shearlet transform (NSST) domain combined with a spiking cortical model (SCM) and improved fuzzy C-means clustering model (FCM) is proposed. First, the infrared target information in the source infrared image is extracted by the FCM. Subsequently, the NSST is used to decompose the target and background areas of the infrared and visible images to obtain their own high- and low-frequency sub-band images. Subsequently, different fusion strategies are adopted for different regions, and the SCM and improved time matrix are adopted for high-frequency background regions. The final fused image is obtained by using the NSST inverse transform. Simulation experiments show that, compared with other methods, the fusion image obtained by this algorithm has a prominent infrared target and intricate texture details in subjective vision, and its information entropy and edge retention factor are optimal for objective evaluation.
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    • References (20)
  • [1]
    王文卿, 高钰迪, 刘涵, 等. 基于低秩稀疏表示的红外与可见光图像序列融合方法[J]. 西安理工大学学报, 2019, 35(3): 276-283. https://www.cnki.com.cn/Article/CJFDTOTAL-XALD201903003.htm

    WANG W Q, GAO Y D, LIU H, et al. Infrared and visible image sequence fusion via low-rank and sparse representation[J]. Journal of Xi 'an University of Technology, 2019, 35(3): 276-283. https://www.cnki.com.cn/Article/CJFDTOTAL-XALD201903003.htm
    [2]
    白玉, 侯志强, 刘晓义, 等. 基于可见光图像和红外图像决策级融合的目标检测算法[J]. 空军工程大学学报(自然科学版), 2020, 21(6): 53-59, 100. https://www.cnki.com.cn/Article/CJFDTOTAL-KJGC202006009.htm

    BAI Y, HOU Z Q, LIU X Y, et al. An object detection algorithm based on decision-level fusion of visible light image and infrared images[J]. Journal of Air Force Engineering University, 2020, 21(6): 53-59, 100. https://www.cnki.com.cn/Article/CJFDTOTAL-KJGC202006009.htm
    [3]
    张林发, 张榆锋, 王琨, 等. 基于直觉模糊集和亮度增强的医学图像融合[J/OL]. 计算机应用, 2021, 41(7): 2082-2091.

    ZHANG L F, ZHANG Y F, WANG K, et al. Medical image fusion with intuitionistic fuzzy set and intensity enhancement[J]. Computer Application, 2021, 41(7): 2082-2091.
    [4]
    江泽涛, 吴辉, 周哓玲. 基于改进引导滤波和双通道脉冲发放皮层模型的红外与可见光图像融合算法[J]. 光学学报, 2018, 38(2): 0210002. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201802015.htm

    JIANG Z T, WU H, ZHOU Q L, et al. 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. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201802015.htm
    [5]
    李玉峰, 尹婷婷. 采用NSCT与FCM相结合的SAR和多光谱图像融合算法[J]. 信号处理, 2017, 33(11): 1523-1529. https://www.cnki.com.cn/Article/CJFDTOTAL-XXCN201711014.htm

    LI Y F, YIN T T. The SAR and multispectral image fusion algorithm based on NSCT and FCM[J]. Signal Processing, 2017, 33(11): 1523-1529. https://www.cnki.com.cn/Article/CJFDTOTAL-XXCN201711014.htm
    [6]
    GONG J M, XUE M L, REN F, et al. Infrared and visible image fusion based on nonsubsampled shearlet transform and fuzzy C-means clustering[J]. Journal of Electronic Imaging, 2018, 27(4): 1-11
    [7]
    Easley G, Labate D, Lim W Q. Sparse directional image representations using the discrete shearlet transform[J]. Applied and Computational Harmonic Analysis, 2008, 25(1): 25-46.
    [8]
    高国荣, 刘艳萍. 基于非抽样Shearlet变换的红外与可见光图像融合方法[J]. 农业机械学报, 2014, 45(3): 268-274. https://www.cnki.com.cn/Article/CJFDTOTAL-NYJX201403044.htm

    GAO G R, LIU Y P. Infrared and visible light image fusion algorithm based on non-subsampled Shearlet transform[J]. Journal of Agricultural Machinery, 2014, 45(3): 268-274. https://www.cnki.com.cn/Article/CJFDTOTAL-NYJX201403044.htm
    [9]
    邢笑雪. 基于NSST的图像融合算法研究[D]. 长春: 吉林大学, 2014: 24-25.

    XING X X. Research on Image Fusion Algorithm Based on NSST[D]. Changchun: Jilin University, 2014: 24-25.
    [10]
    ZHAN K, ZHANG H J, MA Y D. New spiking cortical model for invariant texture retrieval and image processing[J]. IEEE Transactions on Neural Networks, 2009, 20(12): 1980-1986.
    [11]
    江泽涛, 何玉婷, 张少钦. 一种基于对比度增强和柯西模糊函数的红外与弱可见光图像融合算法[J]. 光子学报, 2019, 48(6): 149-158. https://www.cnki.com.cn/Article/CJFDTOTAL-GZXB201906019.htm

    JIANG Z T, HE Y T, ZHANG S Q. Infrared and low-light-level visible image fusion algorithm based on contrast enhancement and cauchy fuzzy function[J]. Acta Photonica Sinica, 2019, 48(6): 149-158. https://www.cnki.com.cn/Article/CJFDTOTAL-GZXB201906019.htm
    [12]
    王念一. 脉冲发放皮层模型图像融合技术研究[D]. 兰州: 兰州大学, 2014: 18-20.

    WANG N Y. Spiking Cortical Mode for Image Fusion[D]. Lanzhou: Lanzhou University, 2014: 18-20.
    [13]
    HE K J, ZHOU D M, ZHANG X J, et al. Infrared and visible image fusion combining interesting region detection and nonsubsampled contourlet transform[J]. Journal of Sensors, 2018, 2018: 1-15.
    [14]
    LEI T, JIA L, HE L, et al. Significantly fast and robust fuzzy C-means clustering algorithm based on morphological reconstruction and membership filtering)[J]. IEEE Transactions on Fuzzy System, 2018: 26(5): 3027-3041.
    [15]
    LIU Z Y, DING F, XU Y, et al. Background dominant colors extraction method based on color image quick fuzzy c-means clustering algorithm[J]. Defence Technology, 2020, 16(5): 1073-1087. http://www.sciengine.com/doi/pdf/E5EAB5B1AAB44FC2A5DB838214E14B6B
    [16]
    刘帅奇, 郑伟, 赵杰, 等. 数字图像融合算法分析与应用[M]. 北京: 机械工业出版社, 2018: 115-116.

    LIU S Q, ZHENG W, ZHAO J, et al. Analysis and Application of Digital Image Fusion Algorithm[M]. Beijing: China Machine Press, 2018: 115-116.
    [17]
    CHEN J, LI X J, LUO L B, et al. Infrared and visible image fusion based on target-enhanced multiscale transform decomposition[J]. Information Sciences, 2020, 508: 64-78.
    [18]
    ZHANG Y, ZHANG L J, BAI X Z, et al. Infrared and visual image fusion through infrared feature extraction and visual information preservation[J]. Infrared Physics and Technology, 2017, 83: 227-237.
    [19]
    MA J L, ZHOU Z Q, WANG B, et al. Infrared and visible image fusion based on visual saliency map and weighted least square optimization[J]. Infrared Physics and Technology, 2017, 82: 8-17.
    [20]
    Xydeas C S, Petrovic V. Objective image fusion performance measure[J]. Electronics Letters, 2000, 36(4): 308-309.
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