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Volume 45 Issue 8
Aug.  2023
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XU Haiyang, ZHAO Wei, LIU Jianye. Infrared and Visible Image Registration Algorithm Based on Edge Structure Features[J]. Infrared Technology , 2023, 45(8): 858-862.
Citation: XU Haiyang, ZHAO Wei, LIU Jianye. Infrared and Visible Image Registration Algorithm Based on Edge Structure Features[J]. Infrared Technology , 2023, 45(8): 858-862.
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Infrared and Visible Image Registration Algorithm Based on Edge Structure Features

  • College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China

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  • Received Date: May 18, 2021
  • Revised Date: June 21, 2021
    Graphical Abstract
    • Abstract
  • Here, a registration algorithm based on edge structure features is proposed to solve the difficulty of extracting feature points from infrared and visible images. First, the structural features of infrared images are enhanced using an optimized saliency algorithm. Second, we extract the stable edge structures of the infrared and visible images using a phase consistency algorithm. Further, the ORB feature points are extracted from the edge structures. Finally, the KNN algorithm and cosine similarity are combined to filter the matching feature points, and the random sample consensus (RANSAC) algorithm is used for purification. Experimental results show that the algorithm overcomes the influence of grayscale differences between infrared and visible images. In addition, it achieves a high registration accuracy and efficiency, which is conducive to the registration of infrared and visible images.
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    • References (13)
  • [1]
    CHEN Yanjia. Visible and infrared image registration based on region features and edginess[J]. Machine Vision and Applications, 2018, 29(1): 113-123. DOI: 10.1007/s00138-017-0879-6
    [2]
    ZENG Qiang. Real-time adaptive visible and infrared image registration based on morphological gradient and C_SIFT[J]. Journal of Real-Time Image Processing, 2019: 1-13.
    [3]
    CHEN S, LI X, ZHAO L, et al. Medium-low resolution multisource remote sensing image registration based on SIFT and robust regional mutual information[J]. International Journal of Remote Sensing, 2018, 39(10): 3215-3242. DOI: 10.1080/01431161.2018.1437295
    [4]
    XU W, ZHONG S, YAN L, et al. Moving object detection in aerial infrared images with registration accuracy prediction and feature points selection[J]. Infrared Physics & Technology, 2018, 92: 318-26.
    [5]
    张莉, 李彬, 田联房, 等. 基于局部结构张量-互信息的多模态图像配准[J]. 华南理工大学学报: 自然科学版, 2017, 45(7): 98-106. https://www.cnki.com.cn/Article/CJFDTOTAL-HNLG201707014.htm

    ZHANG Li, LI Bin, TIAN Lianfang, et al. Multi-modal image registration on the basis of local structure tensor-mutual information[J]. Journal of South China University of Technology: Natural Science Edition, 2017, 45(7): 98-106. https://www.cnki.com.cn/Article/CJFDTOTAL-HNLG201707014.htm
    [6]
    吴延海, 张程, 张烨. 基于梯度信息和区域互信息的图像配准[J]. 广西大学学报: 自然科学版, 2017, 42(2): 720-727. https://www.cnki.com.cn/Article/CJFDTOTAL-GXKZ201702040.htm

    WU Yanhai, ZHANG Cheng, ZHANG Ye. Image registration based on gradient and regional mutual information[J]. Journal of Guangxi University: Natural Science Edition, 2017, 42(2): 720-727. https://www.cnki.com.cn/Article/CJFDTOTAL-GXKZ201702040.htm
    [7]
    XIANG Y, WANG F, YOU H. OS-SIFT: a robust SIFT-like algorithm for high-resolution optical-to-SAR image registration in suburban areas[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(6): 3078-3090. DOI: 10.1109/TGRS.2018.2790483
    [8]
    张晨光, 周诠, 回征. 基于SIFT特征点检测的低复杂度图像配准算法[J]. 扬州大学学报: 自然科学版, 2018, 21(4): 52-56. https://www.cnki.com.cn/Article/CJFDTOTAL-YZDZ201804012.htm

    ZHANG Chenguang, ZHOU Quan, HUI Zheng. A low-complexity image registration approach based on SIFT[J]. Journal of Yangzhou University: Nature Science Edition, 2018, 21(4): 52-56. https://www.cnki.com.cn/Article/CJFDTOTAL-YZDZ201804012.htm
    [9]
    SHENG H. Medical image registration method based on tensor voting and Harris corner point detection[J]. Journal of Medical Imaging and Health Informatics, 2018, 8(3): 583-589. DOI: 10.1166/jmihi.2018.2322
    [10]
    MENG Z. Image registration method based on optimized SURF algorithm[J]. American Journal of Optics and Photonics, 2019, 7(4): 63-69. DOI: 10.11648/j.ajop.20190704.11
    [11]
    Morrone M Concetta, Ross John, Burr David C, et al. Mach bands are phase dependent[J]. Nature, 1986, 324: 250-253. DOI: 10.1038/324250a0
    [12]
    LV L T, YUAN Q Q, LI Z X. An algorithm of iris feature-extracting based on 2D log-gabor[J]. Multi-media Tools and Applications, 2019, 78(16): 22643-22666. DOI: 10.1007/s11042-019-7551-2
    [13]
    Ethan Rublee, Vincent Rabaud, Kurt Konolige, et al. ORB: an efficient alternative to SIFT or SURF[C]//Proceedings of IEEE International Conference on Computer Vision, 2011: 2564-2571.
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