YANG Jiuzhang, LIU Weijian, CHENG Yang. Asymmetric Infrared and Visible Image Fusion Based on Contrast Pyramid and Bilateral Filtering[J]. Infrared Technology , 2021, 43(9): 840-844.
Citation: YANG Jiuzhang, LIU Weijian, CHENG Yang. Asymmetric Infrared and Visible Image Fusion Based on Contrast Pyramid and Bilateral Filtering[J]. Infrared Technology , 2021, 43(9): 840-844.

Asymmetric Infrared and Visible Image Fusion Based on Contrast Pyramid and Bilateral Filtering

More Information
  • Received Date: January 11, 2021
  • Revised Date: February 01, 2021
  • This study proposes an asymmetric infrared and visible image fusion method based on a contrast pyramid to save the feature information of infrared image and the detail information of visible image simultaneously. First, the contrast pyramid is used to decompose the high-frequency and low-frequency information of the infrared and visible images; then, the high-frequency part is fused by taking the largest absolute value, and the low-frequency part is processed differently by the method based on bilateral filtering. Second, the inverse transform of the contrast pyramid was used to obtain the fused image. Subjective visual and objective index evaluations were conducted on the fused image. The results show that the algorithm performs well in highlighting the target feature information and retaining detailed feature information.
  • [1]
    Waxman A M, Gove A N, Fay D A, et al. Color night vision: opponent processing in the fusion of visible and IR imagery[J]. Neural Networks, 1997, 10(1): 1-6. http://www.onacademic.com/detail/journal_1000034198621910_6953.html
    [2]
    XIANG T, YAN L, GAO R. A fusion algorithm for infrared and visible images based on adaptive dual-channel unit-linking PCNN in NSCT domain[J]. Infrared Physics & Technology, 2015, 69: 53-61. http://www.onacademic.com/detail/journal_1000037435766010_b6cd.html
    [3]
    ZHAO J, GAO X, CHEN Y, et al. Multi-window visual saliency extraction for fusion of visible and infrared images[J]. Infrared Physics & Technology, 2016, 76: 295-302. http://smartsearch.nstl.gov.cn/paper_detail.html?id=4f0b14c597a48653341d44502ab3dc75
    [4]
    YAN L, CAO J, Rizvi S, et al. Improving the performance of image fusion based on visual saliency weight map combined with CNN[J]. IEEE Access, 2020, 8(99): 59976-59986. http://ieeexplore.ieee.org/document/9044861
    [5]
    Lewis J J, Robert J. O'Callaghan, Nikolov S G, et al. Pixel- and region-based image fusion with complex wavelets[J]. Information Fusion, 2007, 8(2): 119-130. DOI: 10.1016/j.inffus.2005.09.006
    [6]
    赵立昌, 张宝辉, 吴杰, 等. 基于灰度能量差异性的红外与可见光图像融合[J]. 红外技术, 2020, 42(8): 775-782. http://hwjs.nvir.cn/article/id/hwjs202008012

    ZHAO Lichang, ZHANG Baohui, WU Jie, et al. Fusion of infrared and visible images based on gray energy difference[J]. Infrared Technology, 2020, 42(8): 775-782. http://hwjs.nvir.cn/article/id/hwjs202008012
    [7]
    崔晓荣, 沈涛, 黄建鲁, 等. 基于BEMD改进的视觉显著性红外和可见光图像融合[J]. 红外技术, 2020, 42(11): 1061-1071. http://hwjs.nvir.cn/article/id/c89c0447-6d07-4a75-99f6-1bf8681cf588

    CUI Xiaorong, SHEN Tao, HUANG Jianlu, et al. Infrared and visible image fusion based on bemd and improved visual saliency[J]. Infrared Technology, 2020, 42(11): 1061-1071. http://hwjs.nvir.cn/article/id/c89c0447-6d07-4a75-99f6-1bf8681cf588
    [8]
    李辰阳, 丁坤, 翁帅, 等. 基于改进谱残差显著性图的红外与可见光图像融合[J]. 红外技术, 2020, 42(11): 1042-1047. http://hwjs.nvir.cn/article/id/6e57a6fb-ba92-49d9-a000-c00e7a933365

    LI Chenyang, DING Kun, WENG Shuai, et al. Image fusion of infrared and visible images based on residual significance[J]. Infrared Technology, 2020, 42(11): 1042-1047. http://hwjs.nvir.cn/article/id/6e57a6fb-ba92-49d9-a000-c00e7a933365
    [9]
    ZHOU Z, WANG B, LI S, et al. Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with Gaussian and bilateral filters[J]. Information Fusion, 2016, 30: 1-13. DOI: 10.1016/j.inffus.2015.11.002
    [10]
    Toet A. Image fusion by a ratio of low-pass pyramid[J]. Pattern Recognition Letters, 1989, 9: 245-253. DOI: 10.1016/0167-8655(89)90003-2
    [11]
    Akerman A. Pyramidal techniques for multisensor fusion[C]// Proceedings of SPIE the International Society for Optical Engineering, 1992, 1828: 124-131.
    [12]
    LI Huafeng, QIU Hongmei, YU Zhengtao, et al. Infrared and visible image fusion scheme based on NSCT and low-level visual features[J]. Infrared Physics and Technology, 2016, 76: 174-184. DOI: 10.1016/j.infrared.2016.02.005
    [13]
    彭进业, 王珺, 何贵青, 等. 基于非下采样Contourlet变换和稀疏表示的红外与可见光图像融合方法[J]. 兵工学报, 2013, 34(7): 815-820. https://www.cnki.com.cn/Article/CJFDTOTAL-BIGO201307003.htm

    PENG Jinye, WANG Jun, HE Guiqing, et al. Fusion method for visible and infrared images based on non-subsampled Contourlet transform and sparse representation[J]. Acta Armamentarii, 2013, 34(7): 815-820. https://www.cnki.com.cn/Article/CJFDTOTAL-BIGO201307003.htm
    [14]
    Pajares G, Jesús Manuel de la Cruz. A wavelet-based image fusion tutorial[J]. Pattern Recognition, 2004, 37(9): 1855-1872. DOI: 10.1016/j.patcog.2004.03.010
    [15]
    朱攀, 刘泽阳, 黄战华. 基于DTCWT和稀疏表示的红外偏振与光强图像融合[J]. 光子学报, 2017, 46(12): 213-221. https://www.cnki.com.cn/Article/CJFDTOTAL-GZXB201712028.htm

    ZHU Pan, LIU Zeyang, HUANG Zhanhua. Infrared polarization and intensity image fusion based on dual-tree complex wavelet transform and sparse representation[J]. Acta Photonica Sinica, 2013, 34(7): 815-820. https://www.cnki.com.cn/Article/CJFDTOTAL-GZXB201712028.htm
  • Related Articles

    [1]HAO Jinhu, DU Yuhong, WANG Shuai, REN Weijia. Infrared Image Enhancement Algorithm Based on Wavelet Transform and Improved Bilateral Filtering[J]. Infrared Technology , 2024, 46(9): 1051-1059.
    [2]YANG Yanchun, LEI Huiyun, YANG Wanxuan. Infrared and Visible Image Fusion Based on Fast Joint Bilateral Filtering and Improved PCNN[J]. Infrared Technology , 2024, 46(8): 892-901.
    [3]NIE Fengying, HOU Lixia, WAN Liyong. Infrared Image Enhancement Based on Adaptive Bilateral Filtering and Directional Gradient[J]. Infrared Technology , 2022, 44(12): 1309-1315.
    [4]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.
    [5]YUAN Jingzhen, JIN Wang. Multi-scale Moving Target Detection Method Based on Improved Bilateral Filtering[J]. Infrared Technology , 2019, 41(8): 772-777.
    [6]ZHANG Aijie, LIU Shijian, ZHANG Rui, LI Bing. Design of a Bilateral Filter Based on FPGA[J]. Infrared Technology , 2019, 41(1): 13-17.
    [7]MAO Chen, QIAN Wei-xian, GU Guo-hua, LI Chao. Harris Corner Detection Based on Bilateral Filtering[J]. Infrared Technology , 2014, (10): 812-815,819.
    [8]WANG Shu-peng, GAO Teng. Destriping Method for Infrared Image Based on Bilateral Filter[J]. Infrared Technology , 2014, (9): 728-731.
    [9]A New Improved Bilateral Filtering Algorithm for the Fruit Image Based on Wavelet Transform Domain[J]. Infrared Technology , 2014, (3): 196-199,204.
    [10]ZENG Ya-qiong, CHEN Qian. Dim and Small Target Background Suppression Based on Improved Bilateral Filtering for Single Infrared Image[J]. Infrared Technology , 2011, 33(9): 537-540. DOI: 10.3969/j.issn.1001-8891.2011.09.011
  • Cited by

    Periodical cited type(13)

    1. 尚宇辉,孟伟,房健,王雪峰. 改进径向基函数插值法的多聚焦图像滤波融合. 计算机仿真. 2024(02): 222-226 .
    2. 蒋文娟,刘经天,邵开丽. 激光雷达融合机器视觉的物流分拣多目标视频跟踪. 激光杂志. 2024(06): 221-226 .
    3. 张清蓉,陈龙灿,刘庆. 视频前景区域运动目标姿态识别仿真. 计算机仿真. 2024(07): 258-262 .
    4. 黄勇斌,郭立强. 基于信息回收和频域金字塔的红外与可见光图像融合算法. 淮阴师范学院学报(自然科学版). 2023(01): 15-20+27 .
    5. 陈锦妮,陈宇洋,李云红,拜晓桦. 基于结构与分解的红外光强与偏振图像融合. 红外技术. 2023(03): 257-265 . 本站查看
    6. 张玉昆,王凯娜,杨明彦. 无人机激光雷达遥感图像超分辨率重建方法. 激光杂志. 2023(03): 143-147 .
    7. 沈微微,张兵,朱亚楠,李项辰,张书瑜. 基于多尺度梯度域引导滤波的弱光照图像增强技术. 激光杂志. 2023(05): 182-186 .
    8. 蒋金鑫. 基于VR的精细动作捕捉算法及其在体育训练中的应用研究. 佳木斯大学学报(自然科学版). 2023(03): 136-140 .
    9. 蒋正帅,张强,陈磊. 基于粗-精立体匹配的激光焊接机器人三维视觉定位研究. 激光杂志. 2023(09): 227-232 .
    10. 李威,李忠民. 一种基于EASSF的红外与可见光图像视觉保真度融合. 红外技术. 2022(07): 686-692 . 本站查看
    11. 谷学静,刘秋月,马冠征,周士兵. 基于双边滤波和词袋模型的图像匹配算法. 激光杂志. 2022(07): 70-74 .
    12. 李永萍,杨艳春,党建武,王阳萍. 基于变换域VGGNet19的红外与可见光图像融合. 红外技术. 2022(12): 1293-1300 . 本站查看
    13. 马恋,马庆禄,付冰琳,王江华. 低照度隧道口视觉融合技术研究. 光子学报. 2022(12): 334-346 .

    Other cited types(14)

Catalog

    Article views (387) PDF downloads (76) Cited by(27)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return