ZHANG Zijun, ZHAO Xu, LI Lianpeng, LIU Ziyu. A Stable Interactive Registration Algorithm-based Infrared and Visible Light Image Registration Method for Unexploded Ordnance Targets[J]. Infrared Technology , 2025, 47(3): 376-384.
Citation: ZHANG Zijun, ZHAO Xu, LI Lianpeng, LIU Ziyu. A Stable Interactive Registration Algorithm-based Infrared and Visible Light Image Registration Method for Unexploded Ordnance Targets[J]. Infrared Technology , 2025, 47(3): 376-384.

A Stable Interactive Registration Algorithm-based Infrared and Visible Light Image Registration Method for Unexploded Ordnance Targets

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  • Received Date: June 09, 2024
  • Revised Date: August 13, 2024
  • A stable interactive registration algorithm (SIRA) based on the Imregtform algorithm is proposed to address issues such as complex image backgrounds, low mutual information, and few effective feature points, leading to registration difficulties in the detection of unexploded ordnance (UXO) using infrared and visible-light imaging techniques. First, the Cpselect algorithm is incorporated to realize the accurate alignment of the key nodes of an image, which are aggregated by arithmetic averaging as the initial matrix. The contrast-limited adaptive histogram equalization (CLAHE) algorithm is incorporated to adaptively segment and equalize the image and avoid contrast over-enhancement, combined with bilinear interpolation to ensure smooth continuity between the regions and a stable iterative alignment process. Matrix Frobenius proximity (MFP) was introduced as an alignment evaluation index to alleviate the volatility of traditional evaluation indices. Experimental results show that SIRA enhanced the alignment efficiency by approximately 4.72× and MFP by 15.47× compared to the Imregtform algorithm. The algorithm exhibited high accuracy and stability for UXO image alignment.

  • [1]
    Sigiel N, Chodnicki M, Socik P, et al. Automatic classification of unexploded ordnance (UXO) based on deep learning neural networks (DLNNS)[J]. Polish Maritime Research, 2024, 31(1): 77-84. DOI: 10.2478/pomr-2024-0008
    [2]
    徐建国, 丁凯, 李阳明. 未爆弹药探测技术发展现状及思考[J]. 中国公共安全, 2020(4): 176-178.

    XU Jianguo, DING Kai, LI Yangming. Development status and thinking of unexploded ammunition detection technology[J]. Public Security in China, 2020(4): 176-178.
    [3]
    International Campaign to Ban Landmines. Landmine Monitor 2023[R]. Geneva: ICBL-CMC, 2023(11): 1-4.
    [4]
    陈栋, 闫小伟, 石胜斌. 地表未爆子弹药检测与识别定位技术研究综述[J]. 航空兵器, 2023, 30(5): 1-10.

    CHEN Dong, YAN Xiaowei, SHI Shengbin. A review of research on detection and identification of unexploded ammunition on the ground[J]. Aviation Weaponry, 2023, 30(5): 1-10.
    [5]
    刘子玉, 赵旭, 李连鹏, 等. 基于NGG-YOLOv5的空对地UXO目标检测方法[J]. 电光与控制, 2024, 31(3): 70-74.

    LIU Ziyu, ZHAO Xu, LI Lianpeng, et al. Air-to-ground UXO target detection method based on NGG-YOLOv5[J]. Electro-Optics & Control, 2024, 31(3): 70-74.
    [6]
    陆子渊, 何勇, 卞雷祥, 等. 基于一发多收线圈阵列的频域电磁法未爆弹探测技术[J]. 电子测量与仪器学报, 2023, 37(5): 79-87.

    LU Ziyuan, HE Yong, BIAN Leixiang, et al. Frequency domain electromagnetic unexploded bomb detection technology based on multiple-receive coil array[J]. Journal of Electronic Measurement and Instrumentation, 2023, 37(5): 79-87.
    [7]
    薄瑞, 张志杰, 陈昊泽. 一种新型未爆弹探测传感器的仿真研究[J]. 传感技术学报, 2022, 35(2): 171-178.

    BO Rui, ZHANG Zhijie, CHEN Haoze. Simulation study of a new type of unexploded bomb detection sensor[J]. Journal of Sensor Technology, 2022, 35(2): 171-178.
    [8]
    郝彤, 赵杰. 面向双曲线形态的探地雷达图像识别技术综述[J]. 电子学报, 2019, 47(6): 1366-1372.

    HAO Tong, ZHAO Jie. A review of ground penetrating radar image recognition technology for hyperbolic morphology[J]. Journal of Electronics, 2019, 47(6): 1366-1372.
    [9]
    代牮, 赵旭, 李连鹏, 等. 基于改进YOLOv5的复杂背景红外弱小目标检测算法[J]. 红外技术, 2022, 44(5): 504-512. http://hwjs.nvir.cn/article/id/f71aa5f4-92b0-4570-9056-c2abd5506021

    DAI Jian, ZHAO Xu, LI Lianpeng, et al. Infrared weak small target detection algorithm in complex background based on improved YOLOv5[J]. Infrared Technology, 2022, 44(5): 504-512. http://hwjs.nvir.cn/article/id/f71aa5f4-92b0-4570-9056-c2abd5506021
    [10]
    WU Yanfeng, WANG Yanjie, SUN Haijiang, et al. LSS-target detection in complex sky backgrounds[J]. Chinese Optics, 2019, 12(4): 853-865.
    [11]
    韩自强, 岳明凯, 张骢, 等. 基于孪生网络的无人机目标多模态融合检测[J]. 红外技术, 2023, 45(7): 739-745. http://hwjs.nvir.cn/article/id/2375ef51-29bd-4800-b016-889b652e1674

    HAN Ziqiang, YUE Mingkai, ZHANG Cong, et al. Multimodal fusion detection of UAV targets based on twin networks[J]. Infrared Technology, 2023, 45(7): 739-745. http://hwjs.nvir.cn/article/id/2375ef51-29bd-4800-b016-889b652e1674
    [12]
    Erin L, Rongjun Q, Jared E, et al. Crater detection from commercial satellite imagery to estimate unexploded ordnance in Cambodian agricultural land[J]. PloS, 2020, 15(3): 1-22. http://www.socolar.com/Article/Index?aid=100080575198&jid=100000000003
    [13]
    Ahmed B, Ishan B, Krishan K, et al. A comprehensive review on landmine detection using deep learning techniques in 5G environment: open issues and challenges[J]. Neural Computing and Applications, 2022, 34(24): 21657-21676. DOI: 10.1007/s00521-022-07819-9
    [14]
    职玉, 朱娟娟, 刘锐, 等. 应用特征轮廓四边形的热红外图与可见光图配准[J]. 红外与激光工程, 2021, 50(S2): 171-180.

    ZHI Yu, ZHU Juanjuan, LIU Rui, et al. Registration of thermal infrared image and visible light image using feature contour quadrilateral[J]. Infrared and Laser Engineering, 2021, 50(S2): 171-180.
    [15]
    Chiliaeva V, Almansa A, Ferrec Y, et al. Impact of image registration errors on the quality of hyperspectral images in imaging static Fourier transform spectrometry[J]. Optics Express, 2024, 32(5): 7012-7029.
    [16]
    WEI G, CHEN H, LIN E, et al. Identification of water layer presence in paddy fields using UAV-based visible and thermal infrared imagery[J]. Agronomy, 2023, 13(7): 1932.
    [17]
    TAO S. Multi-sensor remote sensing image alignment based on fast algorithms[J]. Journal of Intelligent Systems, 2023, 13(7): 1932.
    [18]
    JIA W G, GANG L, MENG Z L. Damage detection for rotating blades using digital image correlation with an AC-SURF matching algorithm[J]. Sensors, 2022, 22(21): 8110-8110. http://www.keyanzhidian.com/doc/detail?id=2073189445
    [19]
    CHENG M, ZHANG L, LIU L. An augmented reality image registration method based on improved ORB[J]. Journal of Physics Conference Series, 2020, 1544(1): 012113.
    [20]
    LIANG Z, YANLEI D, HUIPING L, et al. A novel region-based image registration method for multisource remote sensing images Via CNN[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021(14): 1821-1831.
    [21]
    SHENG L, XIU L, ZHEN H G. An adaptive region-based transformer for nonrigid medical image registration with a self-constructing latent graph[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023(7): 1-15.
    [22]
    王程, 王巍, 杨馨, 等. 基于区域特征优化及边缘增强的多聚焦图像融合[J]. 计算机技术与发展, 2024, 34(4): 62-69.

    WANG Cheng, WANG Wei, YANG Xin, et al. Multi-focus image fusion based on regional feature optimization and edge enhancement[J]. Computer Technology and Development, 2024, 34(4): 62-69.
    [23]
    石雪, 陈进琥, 李洪升, 等. 基于感兴趣窄带区域的同步分割与配准方法及在IGRT中的应用[J]. 自动化学报, 2015, 41(9): 1589-1600.

    SHI Xue, CHEN Jinhu, LI Hongsheng, et al. Synchronous segmentation and registration method based on narrowband region of interest and its application in IGRT[J]. Acta Automatica Sinica, 2015, 41(9): 1589-1600.
    [24]
    回丙伟, 宋志勇, 范红旗, 等. 地/空背景下红外图像弱小飞机目标检测跟踪数据集[J]. 中国科学数据(中英文网络版), 2020, 5(3): 291-302.

    HUI Bingwei, SONG Zhiyong, FAN Hongqi, et al. A dataset for detecting and tracking small aircraft targets in infrared images under/air backgrounds[J]. Chinese Science Data (Chinese and English online version), 2020, 5(3): 291-302.
    [25]
    Hossain M S, Shahriar G M, Syeed M M M, et al. Region of interest (ROI) selection using vision transformer for automatic analysis using whole slide images[J]. Scientifc Reports, 2023(13): 11314.
    [26]
    郑晓俊, 郇中丹, 刘君. 图像配准中方向场正则化模型的适定性和收敛性[J]. 数学学报, 2021, 64(3): 385-404.

    ZHENG Xiaojun, XUN Zhongdan, LIU Jun. Well-posedness and convergence of the orientation field regularization model in image registration[J]. Acta Mathematica Sinica, 2021, 64(3): 385-404.
    [27]
    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.

    LIU Yuting, CHEN Zheng, FU Zhanfang, et al. Infrared image enhancement algorithm based on CLAHE[J]. Laser & Infrared, 2016, 46(10): 1290-1294.

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