Fusion of infrared and visible images based on image enhancement and feature extraction

被引:0
|
作者
Luo, Jinzhe [1 ]
Rong, Chuanzhen [1 ]
Jia, Yongxing [1 ]
Yang, Yu [1 ]
Zhu, Ying [1 ]
机构
[1] Army Engn Univ PLA, Commun Engn Coll, Nanjing, Peoples R China
关键词
image fusion; image enhancement; infrared feature extration; multi-scale image decomposition;
D O I
10.1109/IHMSC.2019.00056
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to obtain night vision fusion image, which is more suitable for human visual perception, this paper proposes an infrared and visible image fusion method based on visible image enhancement and infrared feature extraction. Firstly, guided filtering and dynamic range compression are used to enhance the visible image adaptively. At the same time, the infrared pixel value is used as the index factor to transform the visible image exponentially to extract the infrared feature information. Finally, the hybrid multi-scale decomposition method based on guided filter is used to fuse the images. Experimental results show that the fused image has clear background details, outstanding thermal targets, and is superior to the compared methods, both in the visual quality and objective evaluation.
引用
收藏
页码:212 / 216
页数:5
相关论文
共 50 条
  • [31] Interactive Feature Embedding for Infrared and Visible Image Fusion
    Zhao, Fan
    Zhao, Wenda
    Lu, Huchuan
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 35 (09) : 12810 - 12822
  • [32] Local Saliency Extraction for Fusion of Visible and Infrared Images
    Hua, Weiping
    Zhao, Jufeng
    Cui, Guangmang
    Gong, Xiaoli
    Zhu, Liyao
    COMPUTER VISION, PT II, 2017, 772 : 210 - 221
  • [33] Adjacent Feature Combination Based Adaptive Fusion Network for Infrared and Visible Images
    Xu S.
    Chen X.
    Luo J.
    Cheng X.
    Xiao N.
    Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence, 2022, 35 (12): : 1089 - 1100
  • [34] Infrared and Color Visible Image Sequence Fusion Based on Statistical Model and Image Enhancement
    Zhang, Xiuqiong
    2008 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER THEORY AND ENGINEERING, 2008, : 934 - 937
  • [35] Infrared and Visible Image Fusion Based on Visual Saliency Map and Image Contrast Enhancement
    Liu, Yuanyuan
    Wu, Zhiyong
    Han, Xizhen
    Sun, Qiang
    Zhao, Jian
    Liu, Jianzhuo
    SENSORS, 2022, 22 (17)
  • [36] Infrared and Visible Image Fusion with Significant Target Enhancement
    Huo, Xing
    Deng, Yinping
    Shao, Kun
    ENTROPY, 2022, 24 (11)
  • [37] FAST NEAR INFRARED FUSION-BASED ADAPTIVE ENHANCEMENT OF VISIBLE IMAGES
    Elliethy, Ahmed
    Aly, Hussein A.
    2017 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2017), 2017, : 156 - 160
  • [38] Infrared and Visible Image Fusion Based on Multiclassification Adversarial Mechanism in Feature Space
    Zhang H.
    Ma J.
    Fan F.
    Huang J.
    Ma Y.
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2023, 60 (03): : 690 - 704
  • [39] DAE-Nest: A depth information extraction and enhancement fusion network for infrared and visible images
    Shi, Peicheng
    Mao, Fei
    Zhang, Rongyun
    OPTICS COMMUNICATIONS, 2024, 560
  • [40] Fusion of infrared and visible light images based on the grey theory to object extraction
    Wang Chunhua
    Fu Yuchen
    PROCEEDINGS OF 2015 IEEE 12TH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS (ICEMI), VOL. 3, 2015, : 1203 - 1207