LI Wen, YE Kuntao, SHU Leilei, LI Sheng. Infrared and Visible Image Fusion Algorithm Based on Gaussian Fuzzy Logic and Adaptive Dual-Channel Spiking Cortical Model[J]. Infrared Technology , 2022, 44(7): 693-701.
Citation: LI Wen, YE Kuntao, SHU Leilei, LI Sheng. Infrared and Visible Image Fusion Algorithm Based on Gaussian Fuzzy Logic and Adaptive Dual-Channel Spiking Cortical Model[J]. Infrared Technology , 2022, 44(7): 693-701.

Infrared and Visible Image Fusion Algorithm Based on Gaussian Fuzzy Logic and Adaptive Dual-Channel Spiking Cortical Model

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  • Received Date: May 19, 2021
  • Revised Date: August 04, 2021
  • To overcome the shortcomings of current infrared and visible image fusion algorithms, such as non-prominent targets and the loss of many textural details, a novel infrared and visible image fusion algorithm based on Gaussian fuzzy logic and the adaptive dual-channel spiking cortical model (ADCSCM) is proposed in this paper. First, the source infrared and visible images are decomposed into low- and high-frequency parts by non-subsampled shearlet transform (NSST). Then, these are combined with the new sum of the Laplacian and Gaussian fuzzy logic, and dual thresholds are set to guide the fusion of the low-frequency part; simultaneously, the fusion rule based on the ADCSCM is used to guide the fusion of the high-frequency part. Finally, the fused low- and high-frequency parts are reconstructed using inverse NSST to obtain the fused image. The experimental results show that the proposed algorithm has the best subjective visual effect and is better than the other seven fusion algorithms in terms of mutual information, information entropy, and standard deviation. Furthermore, the proposed algorithm can effectively highlight the infrared target, retain more textural details, and improve the quality of the fused image.
  • [1]
    刘佳, 李登峰. 马氏距离与引导滤波加权的红外与可见光图像融合[J]. 红外技术, 2021, 43(2): 162-169. http://hwjs.nvir.cn/article/id/56484763-c7b0-4273-a087-8d672e8aba9a

    LIU Jia, LI Dengfeng. Infrared and visible light image fusion based on mahalanobis distance and guided filter weight-ing[J]. Infrared Technology, 2021, 43(2): 162-169. http://hwjs.nvir.cn/article/id/56484763-c7b0-4273-a087-8d672e8aba9a
    [2]
    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 Zetao, HE Yuting, ZHANG Shaoqin. 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
    [3]
    MA J, ZHOU Z, WANG B, et al. Infrared and visible image fusion based on visual saliency map and weighted least square optimization[J]. Infrared Physics & Technology, 2017, 82: 8-17.
    [4]
    王建, 吴锡生. 基于改进的稀疏表示和PCNN的图像融合算法研究[J]. 智能系统学报, 2019, 14(5): 922-928. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNXT201905011.htm

    WANG Jian, WU Xisheng. Image fusion based on the improved sparse representation and PCNN[J]. CAAI Transactions on Intelligent Systems, 2019, 14(5): 922-928. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNXT201905011.htm
    [5]
    LIU Z, FENG Y, CHEN H, et al. A fusion algorithm for infrared and visible based on guided filtering and phase congruency in NSST domain[J]. Optics & Lasers in Engineering, 2017, 97: 71-77.
    [6]
    邓立暖, 尧新峰. 基于NSST的红外与可见光图像融合算法[J]. 电子学报, 2017, 45(12): 2965-2970. DOI: 10.3969/j.issn.0372-2112.2017.12.019

    DENG Linuan, YAO Xinfeng. Research on the fusion algorithm of infrared and visible images based on non-subsampled shearlet transform[J]. Acta Electronica Sinica, 2017, 45(12): 2965-2970. DOI: 10.3969/j.issn.0372-2112.2017.12.019
    [7]
    王聪, 钱晨, 孙伟, 等. 基于SCM和CST的红外与可见光图像融合算法[J]. 红外技术, 2016, 38(5): 396-402. http://hwjs.nvir.cn/article/id/hwjs201605007

    WANG Cong, QIAN Chen, SUN Wei, et al. Infrared and visible images fusion based on SCM and CST[J]. Infrared Technology, 2016, 38(5): 396-402. http://hwjs.nvir.cn/article/id/hwjs201605007
    [8]
    TAN W, ZHOU H, SONG J, et al. Infrared and visible image perceptive fusion through multi-level Gaussian curvature filtering image decomposition[J]. Applied Optics, 2019, 58(12): 3064-3073. DOI: 10.1364/AO.58.003064
    [9]
    冯贺, 李立, 赵凯. 基于拉普拉斯分解耦合亮度调节的可见光与红外图像融合算法[J]. 电子测量与仪器学报, 2020, 34(10): 91-97. https://www.cnki.com.cn/Article/CJFDTOTAL-DZIY202010011.htm

    FENG He, LI Li, ZHAO Kai. Fusion algorithm of visible and infrared image based on Laplace decomposition coupled with brightness adjustment[J]. Journal of Electronic Measurement and Instrument, 2020, 34(10): 91-97. https://www.cnki.com.cn/Article/CJFDTOTAL-DZIY202010011.htm
    [10]
    GUO K, LABATE D. Optimally sparse multidimensional representation using shearlets[J]. SIAM Journal on Mathematical Analysis, 2007, 39(1): 298-318. DOI: 10.1137/060649781
    [11]
    焦姣, 吴玲达. 向导滤波和NSST相结合的多光谱与全色图像融合算法[J]. 通信学报, 2018, 39(S2): 79-87. https://www.cnki.com.cn/Article/CJFDTOTAL-TXXB2018S2012.htm

    JIAO Jiao, WU Lingda. Multispectral and panchromatic images fusion method based on guided filter and NSST[J]. Journal on Communications, 2018, 39(S2): 79-87. https://www.cnki.com.cn/Article/CJFDTOTAL-TXXB2018S2012.htm
    [12]
    ZHAN K, ZHANG H, MA Y. New spiking cortical model for invariant texture retrieval and image processing[J]. IEEE Transactions on Neural Networks, 2009, 20(12): 1980-1986. DOI: 10.1109/TNN.2009.2030585
    [13]
    ZHAO C, HUANG Y, QIU S. Infrared and visible image fusion algorithm based on saliency detection and adaptive double-channel spiking cortical model[J]. Infrared Physics & Technology, 2019, 102: 102976.
    [14]
    罗娟, 王立平, 谭云兰. 二代Curvelet变换耦合细节度量模型的遥感图像融合算法[J]. 电子测量与仪器学报, 2019, 33(7): 129-136. https://www.cnki.com.cn/Article/CJFDTOTAL-DZIY201907017.htm

    LUO Juan, WANG Liping, TAN Yunlan. Remote sensing image fusion method using second generation curvelet transform coupled with detail metric model[J]. Journal of Electronic Measurement and Instrument, 2019, 33(7): 129-136. https://www.cnki.com.cn/Article/CJFDTOTAL-DZIY201907017.htm
    [15]
    苏金凤, 张贵仓, 汪凯. 结合鲁棒主成分分析和非下采样轮廓波变换的红外与可见光图像的压缩融合[J]. 激光与光电子学进展, 2020, 57(4): 84-93. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ202004008.htm

    SU J F, ZHANG G C, WANG K. Compressed fusion of infrared and visible images combining robust principal component analysis and non-subsampled contour transform[J]. Laser & Optoelectronics Progress, 2020, 57(4): 84-93. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ202004008.htm
    [16]
    YIN S, CAO L, TAN Q, et al. Infrared and visible image fusion based on NSCT and fuzzy logic[C]//Proceedings of the 2010 IEEE International Conference on Mechatronics and Automation, 2010: 671-675.
    [17]
    朱攀, 黄战华. 基于二维经验模态分解和高斯模糊逻辑的红外与可见光图像融合[J]. 光电子·激光, 2017, 28(10): 1156-1162. https://www.cnki.com.cn/Article/CJFDTOTAL-GDZJ201710016.htm

    ZHU Pan, HUANG Zhanhua. Fusion of infrared and visible images based on BEMD and GFL[J]. Journal of Optoelectronics · Laser, 2017, 28(10): 1156-1162. https://www.cnki.com.cn/Article/CJFDTOTAL-GDZJ201710016.htm
    [18]
    闫利, 向天烛. NSCT域内结合边缘特征和自适应PCNN的红外与可见光图像融合[J]. 电子学报, 2016, 44(4): 761-766. DOI: 10.3969/j.issn.0372-2112.2016.04.002

    YAN Li, XIANG Tianzhu. Fusion of infrared and visible based on edge feature and adaptive PCNN in NSCT domain[J]. Acta Electronica Sinica, 2016, 44(4): 761-766. DOI: 10.3969/j.issn.0372-2112.2016.04.002
    [19]
    侯瑞超, 周冬明, 聂仁灿, 等. 结合HSI变换与双通道脉冲发放皮层的彩色多聚焦图像融合[J]. 云南大学学报: 自然科学版, 2019, 41(2): 245-252. https://www.cnki.com.cn/Article/CJFDTOTAL-YNDZ201902006.htm

    HOU Ruichao, ZHOU Dongming, NIE Rencan, et al. Multi-focus color image fusion using HSI transform and dual channel spiking cortical model[J]. Journal of Yunnan University: Natural Sciences Edition, 2019, 41(2): 245-252. https://www.cnki.com.cn/Article/CJFDTOTAL-YNDZ201902006.htm
    [20]
    Nencini F, Garzelli A, Baronti S, et al. Remote sensing image fusion using the curvelet transform[J]. Information Fusion, 2007, 8(2): 143-156. DOI: 10.1016/j.inffus.2006.02.001
    [21]
    ZHANG Q, Guo B. Multifocus image fusion using the nonsubsampled contourlet transform[J]. Signal Process, 2009, 89(7): 1334-1346. DOI: 10.1016/j.sigpro.2009.01.012
    [22]
    MA J, CHEN C, LI C, et al. Infrared and visible image fusion via gradient transfer and total variation minimization[J]. Information Fusion, 2016, 31: 100-109. DOI: 10.1016/j.inffus.2016.02.001
    [23]
    QU X, YAN J, XIAO H, et al. Image fusion algorithm based on spatial frequency-motivated pulse coupled neural networks in nonsubsampled contourlet transform domain[J]. Acta Automatica Sinica, 2008, 34(12): 1508-1514. DOI: 10.1016/S1874-1029(08)60174-3
    [24]
    YIN M, LIU X, LIU Y, et al. Medical image fusion with parameter-adaptive pulse coupled neural network in nonsubsampled shearlet transform domain[J]. IEEE Transactions on Instrumentation and Measurement, 2019, 68(1): 49-64. DOI: 10.1109/TIM.2018.2838778
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