Projection Shape Template-Based Ship Target Recognition in TerraSAR-X Images

被引:52
|
作者
Zhu, Jiwei [1 ,2 ,3 ]
Qiu, Xiaolan [1 ,2 ]
Pan, Zongxu [1 ,2 ]
Zhang, Yueting [1 ,2 ]
Lei, Bin [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Elect, Beijing 100190, Peoples R China
[2] Chinese Acad Sci, Key Lab Spatial Informat Proc & Applicat Syst Tec, Beijing 100190, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
Contour extraction; projection shape template (PST); ship recognition; synthetic aperture radar (SAR) image; SAR IMAGES; VESSEL CLASSIFICATION; FEATURES;
D O I
10.1109/LGRS.2016.2635699
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Ship target recognition has always been a hot issue in the field of ocean surveillance. Due to the serious shortage of samples in ship target recognition for synthetic aperture radar (SAR) images, the template-based method is still one of the most effective ways to solve the problem. In this letter, we put forward a novel ship recognition method based on the projection shape template (PST), aiming at increasing both the accuracy and the robustness of the recognition. The PST of each category is calculated by projecting the 3-D model obtained from the two-view images of the target to the 2-D slant-plane image according to the SAR imaging model. Then, we propose a contour extraction method to detect the profile of ships, which served as the feature. Finally, the identity of the query ship is obtained through contour matching. Experimental results indicate that the proposed method is effective even when the number of samples is extremely small, consequently providing a promising way for the automatic interpretation of ship targets in the SAR images.
引用
收藏
页码:222 / 226
页数:5
相关论文
共 50 条
  • [31] UNSUPERVISED SEGMENTATION OF AGRICULTURAL REGIONS USING TERRASAR-X IMAGES
    Bratsolis, Emmanuel
    2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 1718 - 1721
  • [32] MONITORING THE DEFORMATION OF SHUPING LANDSLIDE WITH TERRASAR-X SPOTLIGHT IMAGES
    Fan Jinghui
    Xia Ye
    Zhao Hongli
    Li Man
    Guo Xiaofang
    Tu Pengfei
    Liu Guang
    Lin Hao
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 29 - 32
  • [33] Research on Moving Target Indication Based on Along Track Interferometry of TerraSAR-X Data
    Jiao J.
    Tian C.
    Huang J.
    Zeng Q.
    Beijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis, 2020, 56 (01): : 164 - 172
  • [34] Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis
    Gui, Rong
    Xu, Xin
    Dong, Hao
    Song, Chao
    Pu, Fangling
    REMOTE SENSING, 2016, 8 (09)
  • [35] SHIP DETECTION WITH QUAD POLARIMETRIC TERRASAR-X DATA: AN ADAPTIVE NOTCH FILTER
    Marino, Armando
    Walker, Nick
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 245 - 248
  • [36] Measuring Subsidence of Transport Infrastructures with Time Series TerraSAR-X Images
    Zhang, Yonghong
    Wu, Hongan
    Liu, Xiaolong
    10TH EUROPEAN CONFERENCE ON SYNTHETIC APERTURE RADAR (EUSAR 2014), 2014,
  • [37] A template-based shape representation technique
    Ebrahim, Yasser
    Ahmed, Maher
    Chau, Siu-Cheung
    Abdelsalam, Wegdan
    IMAGE ANALYSIS AND RECOGNITION, PROCEEDINGS, 2008, 5112 : 497 - +
  • [38] Generation of an optimum target trajectory for the TerraSAR-X repeat observation satellite
    D'Amico, S
    Arbinger, C
    Kirschner, M
    Campagnola, S
    PROCEEDINGS OF THE 18TH INTERNATIONAL SYMPOSIUM ON SPACE FLIGHT DYNAMICS, 2004, 548 : 137 - 142
  • [39] Experimental Demonstration of Staggered Ambiguous SAR Mode for Ship Monitoring With TerraSAR-X
    Ustalli, Nertjana
    Peixoto, Maxwell Nogueira
    Kraus, Thomas
    Steinbrecher, Ulrich
    Krieger, Gerhard
    Villano, Michelangelo
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [40] Combining TerraSAR-X and Landsat Images for Emergency Response in Urban Environments
    Havivi, Shiran
    Schvartzman, Ilan
    Maman, Shimrit
    Rotman, Stanley R.
    Blumberg, Dan G.
    REMOTE SENSING, 2018, 10 (05):