留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

马氏距离与引导滤波加权的红外与可见光图像融合

刘佳 李登峰

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.
引用本文: 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.
LIU Jia, LI Dengfeng. Infrared and Visible Light Image Fusion Based on Mahalanobis Distance and Guided Filter Weighting[J]. Infrared Technology , 2021, 43(2): 162-169.
Citation: LIU Jia, LI Dengfeng. Infrared and Visible Light Image Fusion Based on Mahalanobis Distance and Guided Filter Weighting[J]. Infrared Technology , 2021, 43(2): 162-169.

马氏距离与引导滤波加权的红外与可见光图像融合

基金项目: 

国家自然科学基金项目“稀疏框架与相关问题研究” 61471410

详细信息
    作者简介:

    刘佳(1997-),女,湖北黄冈人,硕士,主研领域:数字图像处理。E-mail:1769723820@qq.com

    通讯作者:

    李登峰(1964-),男,河南开封人,博士,教授,博士生导师,主研领域:小波分析与图像处理

  • 中图分类号: TP391

Infrared and Visible Light Image Fusion Based on Mahalanobis Distance and Guided Filter Weighting

  • 摘要: 为使红外与可见光融合图像获得更好的分辨率和清晰度,提出基于非下采样轮廓波变换(non-subsampled contourlet transform, NSCT)的马氏距离加权拉普拉斯能量和与引导滤波改进(frequency tuned, FT)结合的红外与可见光图像融合算法。首先,对可见光图像进行对比度受限的自适应直方图均衡(contrast limited adaptive histogram equalization, CLAHE),并将红外图像与CLAHE处理后可见光图像进行NSCT变换,分解为低频和高频; 其次,对FT算法使用引导滤波进行改进,利用改进的FT算法提取红外图像显著性图自适应加权融合低频图像,对高频图像使用基于马氏距离加权的拉普拉斯能量和取大融合; 最后,对融合的低频和高频图像进行NSCT逆变换获得融合图像。实验结果表明,该融合方法相较其他传统融合方法,在主观视觉上和客观指标上都有较好的表现。
  • 图  1  NSCT分解过程

    Figure  1.  The decomposition process of NSCT

    图  2  可见光图像对比度增强

    Figure  2.  Visible image contrast enhancement

    图  3  融合框架

    Figure  3.  Fusion framework

    图  4  可见光源图像与红外源图像

    Figure  4.  Source image of visible light image and infrared image

    图  5  实验图像对比

    Figure  5.  The comparison of experimental images

    表  1  融合图像客观评价结果

    Table  1.   Objective evaluation results of fusion image

    Image name Fusion method EI SD AG SF
    Ship   DWT 4.9016 10.4666 1.4100 3.1531
      NSCT 4.9139 10.4807 1.3980 3.1546
      NSCT-FT 5.9540 21.1184 1.6376 3.9024
      NSCT-M 6.5735 25.8154 4.7976 10.1821
    Man   DWT 6.5266 31.5238 2.9829 5.5125
      NSCT 6.5491 31.7851 3.2272 6.3206
      NSCT-FT 7.1864 61.6516 3.4935 7.1168
      NSCT-M 7.6698 58.7864 8.8359 15.5185
    Street   DWT 5.9299 20.6524 3.1668 7.7725
      NSCT 5.9442 21.8888 3.7054 12.7396
      NSCT-FT 5.5269 33.4513 4.0396 13.8090
      NSCT-M 6.8136 41.2933 8.4553 20.3821
    下载: 导出CSV
  • [1] LIU Z, CHAI Y, YIN H, et al. A novel multi-focus image fusion approach based on image decomposition[J]. Information Fusion, 2017, 35: 102-116. doi:  10.1016/j.inffus.2016.09.007
    [2] Mauri G, Cova L, Beni S D, et al. Real-time US-CT/MRI image fusion for guidance of thermal ablation of liver tumors undetectable with US: results in 295 cases[J]. Cardiovasc Intervent Radiol, 2015, 38(1): 143. doi:  10.1007/s00270-014-0897-y
    [3] Tuia D, Marcos D, Camps-Valls G. Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization[J]. Isprs Journal of Photogrammetry & Remote Sensing, 2016, 120: 1-12. http://www.sciencedirect.com/science/article/pii/S0924271616301903
    [4] Baviskar J, Mulla A, Kudu N, et al. Sub-band exchange DWT based image fusion algorithm for enhanced security[C]//International Conference on Advances in Computing, Communications and Informatics of IEEE, 2014: 534-539.
    [5] ZHAO Cheng, HUANG Yongdong, QIU Shi. Infrared and visible image fusion algorithm based on saliency detection and adaptive double-channel spiking cortical model[J]. Infrared Physics and Technology, 2019: 102: 102976. doi:  10.1016/j.infrared.2019.102976
    [6] SONG Minghui, LIU Lu, PENG Yuanxi, et al. Infrared & visible images fusion based on redundant directional lifting-based wavelet and saliency detection[J]. Infrared Physics and Technology, 2019, 101: 45-55. doi:  10.1016/j.infrared.2019.05.017
    [7] 甄媚, 王书朋. 可见光与红外图像自适应加权平均融合方法[J]. 红外技术, 2019, 41(4): 341-346. http://hwjs.nvir.cn/article/id/hwjs201904008

    ZHEN Mei, WANG Shupeng. An adaptive weight average fusion method for visible and infrared images[J]. Infrared Technology, 2019, 41(4): 341-346. http://hwjs.nvir.cn/article/id/hwjs201904008
    [8] 甘玲, 张倩雯. 结合NSCT与引导滤波的图像融合方法[J]. 红外技术, 2018, 40(5): 444-448, 454. http://hwjs.nvir.cn/article/id/hwjs201805007

    GAN Ling, ZHANG Qianwen. Image fusion method combining non-subsampled contourlet transform and guide filtering[J]. Infrared Technology, 2018, 40(5): 444-448, 454. http://hwjs.nvir.cn/article/id/hwjs201805007
    [9] 刘智嘉, 贾鹏, 夏寅辉, 等. 基于红外与可见光图像融合技术发展与性能评价[J]. 激光与红外, 2019, 49(5): 633-640. doi:  10.3969/j.issn.1001-5078.2019.05.021

    LIU Zhijia, JIA Peng, XIA Yinhui, et al. Development and performance evaluation of infrared and visual image fusion technology[J]. Laser and Infrared, 2019, 49(5): 633-640. doi:  10.3969/j.issn.1001-5078.2019.05.021
    [10] 肖儿良, 刘雯雯. 多尺度梯度域可见光与红外热图像融合方法研究[J]. 计算机应用研究, 2015, 32(10): 3160-3163, 3167. doi:  10.3969/j.issn.1001-3695.2015.10.065

    XIAO Erliang, LIU Wenwen. Research of multi-scale gradient domain visible and thermal image fusion method[J]. Application Research of Computers, 2015, 32(10): 3160-3163, 3167. doi:  10.3969/j.issn.1001-3695.2015.10.065
    [11] WANG Shiying, SHEN Yan. Multi-modal image fusion based on saliency guided in NSCT domain[J]. IET Image Processing, 2020, 14(13): 3188-3201. doi:  10.1049/iet-ipr.2019.1319
    [12] 刘斌, 辛迦楠, 谌文江, 等. 不可分拉普拉斯金字塔构造及其在多光谱图像融合中的应用[J]. 计算机应用, 2019, 39(2): 564-570. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY201902045.htm

    LIU Bin, XIN Jianan, CHEN Wenjiang, et al. Construction of non-separable Laplacian pyramid and its application in multi-spectral image fusion[J]. Journal of Computer Applications, 2019, 39(2): 564-570. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY201902045.htm
    [13] Baviskar J, Mulla A, Kudu N, et al. Sub-band exchange DWT based image fusion algorithm for enhanced security[C]//International Conference on Advances in Computing, Communications and Informatics of IEEE, 2014: 534-539.
    [14] 郭全民, 王言, 李翰山. 改进IHS-Curvelet变换融合可见光与红外图像抗晕光方法[J]. 红外与激光工程, 2018, 47(11): 440-448. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201811060.htm

    GUO Quanmin, WANG Yan, LI Hanshan. Anti-halation method of visible and infrared image fusion based on improved IHS-curvelet transform[J]. Infrared and Laser Engineering, 2018, 47(11): 440-448. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201811060.htm
    [15] Do Minh N, Vetterli Martin. The contourlet transform: an efficient directional multiresolution image representation[J]. IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society, 2005, 14(12): 2091-2107. doi:  10.1109/TIP.2005.859376
    [16] 胡顺石, 丁琳, 秦建新, 等. 基于Iαβ色彩空间和Contourlet变换相结合的融合方法[J]. 计算机应用研究, 2010, 27(4): 1521-1523. https://www.cnki.com.cn/Article/CJFDTOTAL-JSYJ201004089.htm

    HU Shunshi, DING Lin, QIN Jianxin. Image fusion technique based on combination of Iαβ color space and contourlet transform[J]. Application Research of Computers, 2010, 27(4): 1521-1523. https://www.cnki.com.cn/Article/CJFDTOTAL-JSYJ201004089.htm
    [17] HOU Yingkun, ZHAO Chunxia, LIU Mingxia. The nonsubsampled contourlet transform: theory, design, and applications[J]. International Conference on Computer Science and Software Engineering of IEEE, 2008, DOI:  10.1109/CSSE.2008.806.
    [18] 刘卷舒, 蒋伟. 改进的基于非下采样的Contourlet变换的图像融合算法[J]. 计算机应用, 2018, 38(S1): 194-197. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY2018S1046.htm

    LIU Juanshu, JIANG Wei. Improved image fusion algorithm based on nonsubsampled Contourlet transform[J]. Journal of Computer Applications, 2018, 38(S1): 194-197. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY2018S1046.htm
    [19] 常诚, 黄国荣, 常雅男, 等. 基于非下采样Contourlet变换的无人机景象匹配算法[J]. 科学技术与工程, 2014, 14(2): 137-140, 171. doi:  10.3969/j.issn.1671-1815.2014.02.032

    CHANG Cheng, HUANG Guorong, CHANG Yanan, et al. Scene matching algorithm for unmanned aerial vehicle based on nonsubsampled contourlet transform[J]. Science Technology and Engineering, 2014, 14(2): 137-140, 171. doi:  10.3969/j.issn.1671-1815.2014.02.032
    [20] 林子慧, 魏宇星, 张建林, 等. 基于显著性图的红外与可见光图像融合[J]. 红外技术, 2019, 41(7): 640-645. http://hwjs.nvir.cn/article/id/hwjs201907008

    LIN Zihui, WEI Yuxing, ZHANG Jianlin, et al. Image fusion of infrared and visible image based on saliency map[J]. Infrared Technology, 2019, 41(7): 640-645. http://hwjs.nvir.cn/article/id/hwjs201907008
    [21] 刘玉婷, 陈峥, 付占方, 等. 基于CLAHE的红外图像增强算法[J]. 激光与红外, 2016, 46(10): 1290-1294. doi:  10.3969/j.issn.1001-5078.2016.10.023

    LIU Yuting, CHEN Zheng, FU Zhanfang, et al. Infrared image enhancement algorithm based on CLAHE[J]. Laser and Infrared, 2016, 46(10): 1290-1294. doi:  10.3969/j.issn.1001-5078.2016.10.023
    [22] Achanta R, Hemami S, Estrada F. Frequency-tuned salient region detection[C]//Computer Vision and Pattern Recognition of IEEE, 2009: DOI: 10.1109/CVPR.2009.5206596.
    [23] 谢伟, 王莉明, 胡欢君, 等. 结合引导滤波的自适应多曝光图像融合[J]. 计算机工程与应用, 2019, 55(4): 193-199. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201904029.htm

    XIE Wei, WANG Liming, HU Huanjun, et al. Adaptive multi-exposure image fusion with guided filtering[J]. Computer Engineering and Applications, 2019, 55(4): 193-199. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201904029.htm
    [24] 孙晓龙, 王正勇, 符耀庆, 等. 基于改进拉普拉斯能量和的快速图像融合[J]. 计算机工程与应用, 2015, 51(5): 193-197. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201505037.htm

    SUN Xiaolong, WANG Zhengyong, FU Yaoqing, et al. Fast image fusion based on sum of modified Laplacian[J]. Computer Engineering and Applications, 2015, 51(5): 193-197. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201505037.htm
    [25] 刘光宇, 庞永杰. 基于阿尔法均值算法和马氏距离的图像自适应滤波[J]. 吉林大学学报: 工学版, 2015, 45(2): 670-674. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201502050.htm

    LIU Guangyu, PANG Yongjie. Filter of the optical image based on alpha-trimmed mean filter and Mahalanobis distance[J]. Journal of Jilin University: Engineering and Technology Edition, 2015, 45(2): 670-674. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201502050.htm
  • 加载中
图(5) / 表(1)
计量
  • 文章访问数:  303
  • HTML全文浏览量:  124
  • PDF下载量:  44
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-03-11
  • 修回日期:  2020-03-19
  • 刊出日期:  2021-02-20

目录

    /

    返回文章
    返回