Infrared and Visible Image Fusion with Hybrid Image Filtering

被引:5
|
作者
Zhang, Yongxin [1 ]
Li, Deguang [1 ]
Zhu, WenPeng [2 ]
机构
[1] Luoyang Normal Univ, Sch Informat Technol, Luoyang 471934, Peoples R China
[2] Northwest Univ, Sch Informat Sci, Xian 710127, Peoples R China
基金
中国国家自然科学基金;
关键词
Image fusion;
D O I
10.1155/2020/1757214
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Image fusion is an important technique aiming to generate a composite image from multiple images of the same scene. Infrared and visible images can provide the same scene information from different aspects, which is useful for target recognition. But the existing fusion methods cannot well preserve the thermal radiation and appearance information simultaneously. Thus, we propose an infrared and visible image fusion method by hybrid image filtering. We represent the fusion problem with a divide and conquer strategy. A Gaussian filter is used to decompose the source images into base layers and detail layers. An improved co-occurrence filter fuses the detail layers for preserving the thermal radiation of the source images. A guided filter fuses the base layers for retaining the background appearance information of the source images. Superposition of the fused base layer and fused detail layer generates the final fusion image. Subjective visual and objective quantitative evaluations comparing with other fusion algorithms demonstrate the better performance of the proposed method.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Infrared and visible image fusion through hybrid curvature filtering image decomposition
    Liu, Guote
    Zhou, Jinhui
    Li, Tong
    Wu, Weiquan
    Guo, Fang
    Luo, Bing
    Chen, Sijun
    [J]. INFRARED PHYSICS & TECHNOLOGY, 2022, 120
  • [2] Infrared and Visible Image Fusion Based on Image Enhancement and Rolling Guidance Filtering
    Liang Jiaming
    Yang Shen
    Tian Lifan
    [J]. LASER & OPTOELECTRONICS PROGRESS, 2023, 60 (02)
  • [3] Multiscale infrared and visible image fusion using gradient domain guided image filtering
    Zhu, Jin
    Jin, Weiqi
    Li, Li
    Han, Zhenghao
    Wang, Xia
    [J]. INFRARED PHYSICS & TECHNOLOGY, 2018, 89 : 8 - 19
  • [4] Infrared and Visible Image Fusion Method Based on NSST and Guided Filtering
    Zhou Jie
    Li Wenjuan
    Zhang Peng
    Luo Jun
    Li Sijing
    Zhao Jiong
    [J]. ICOSM 2020: OPTOELECTRONIC SCIENCE AND MATERIALS, 2020, 11606
  • [5] Infrared and visible image fusion based on saliency and fast guided filtering
    Guo, Zhaoyang
    Yu, Xiantao
    Du, Qinglei
    [J]. INFRARED PHYSICS & TECHNOLOGY, 2022, 123
  • [6] Image Fusion with Guided Image Filtering in NSCT-domain for Infrared and Visible Images of Insulator
    Qi, Yin Cheng
    Cai, Yin Ping
    Zhao, Zhen Bing
    Xu, Lei
    [J]. FRONTIERS OF MANUFACTURING SCIENCE AND MEASURING TECHNOLOGY V, 2015, : 217 - 224
  • [7] Infrared and Visible Image Fusion via Hybrid Variational Model
    Xia, Zhengwei
    Liu, Yun
    Wang, Xiaoyun
    Zhang, Feiyun
    Chen, Rui
    Jiang, Weiwei
    [J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2024, E107D (04) : 569 - 573
  • [8] A Multilevel Hybrid Transmission Network for Infrared and Visible Image Fusion
    Li, Qingqing
    Han, Guangliang
    Liu, Peixun
    Yang, Hang
    Chen, Dianbing
    Sun, Xinglong
    Wu, Jiajia
    Liu, Dongxu
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [9] Infrared and visible image fusion based on hybrid model driving
    Shen, Yu
    Chen, Xiao-Peng
    Liu, Cheng
    Zhang, Hong-Guo
    Wang, Lin
    [J]. Kongzhi yu Juece/Control and Decision, 2021, 36 (09): : 2143 - 2151
  • [10] Infrared and Visible Image Fusion via Rolling Guidance Filtering and Hybrid Multi-Scale Decomposition
    Zhao Cheng
    Huang Yongdong
    [J]. LASER & OPTOELECTRONICS PROGRESS, 2019, 56 (14)