Automated Extraction of Orthorectified Building Layer from High-Resolution Satellite Images

被引:2
|
作者
Kim, Seunghee [1 ]
Kim, Taejung [1 ]
机构
[1] Inha Univ, Dept Geoinformat Engn, Incheon, South Korea
关键词
Orthorectification; Satellite image; True orthoimage; Building database; Digital elevation model;
D O I
10.7780/kjrs.2023.39.3.7
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
As the availability of high-resolution satellite imagery increases, improvement of positioning accuracy of satellite images is required. The importance of orthorectified images is also increasing, which removes relief displacement and establishes true localization of man-made structures. In this paper, we performed automated extraction of building rooftops and total building areas within original satellite images using the existing building height database. We relocated the rooftops in their true position and generated an orthorectified building layer. The extracted total building areas were used to blank out building areas and generate true orthographic non-building layer. A final orthorectified image was provided by overlapping the building layer and non-building layer. We tested the proposed method with KOMPSAT-3 and KOMPSAT3A satellite images and verified the results by overlapping with a digital topographical map. Test results showed that orthorectified building layers were generated with a position error of 0.4 m. Through the proposed method, the feasibility of automated true orthoimage generation within dense urban areas was confirmed.
引用
收藏
页码:339 / 353
页数:15
相关论文
共 50 条
  • [31] Building extraction from high-resolution satellite image for tsunami early damage estimation
    Vu T.T.
    Applied Geomatics, 2011, 3 (2) : 75 - 81
  • [32] Optimized building extraction from high-resolution satellite imagery using deep learning
    Ramesh Raghavan
    Dinesh Chander Verma
    Digvijay Pandey
    Rohit Anand
    Binay Kumar Pandey
    Harinder Singh
    Multimedia Tools and Applications, 2022, 81 : 42309 - 42323
  • [33] Optimized building extraction from high-resolution satellite imagery using deep learning
    Raghavan, Ramesh
    Verma, Dinesh Chander
    Pandey, Digvijay
    Anand, Rohit
    Pandey, Binay Kumar
    Singh, Harinder
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (29) : 42309 - 42323
  • [34] Information extraction from high resolution satellite images
    Yang, Haiping
    Luo, Jiancheng
    Shen, Zhanfeng
    Xia, Liegang
    MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL REMOTE SENSING TECHNOLOGY, TECHNIQUES AND APPLICATIONS V, 2014, 9263
  • [35] Burnt Area Extraction from High-Resolution Satellite Images Based on Anomaly Detection
    Luces, Oscar David Rafael Narvaez
    Pham, Minh-Tan
    Poterek, Quentin
    Braun, Remi
    MACHINE LEARNING AND PRINCIPLES AND PRACTICE OF KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2023, PT III, 2025, 2135 : 448 - 457
  • [36] ROAD EXTRACTION FROM HIGH RESOLUTION SATELLITE IMAGES
    Ozkaya, M.
    XXII ISPRS CONGRESS, TECHNICAL COMMISSION IV, 2012, 39-B4 : 143 - 148
  • [37] Road extraction from high-resolution satellite images using level set methods
    Ma, Zhen
    Wu, Ji-Tao
    Luo, Zhong-Hua
    COMPUTATIONAL MODELLING OF OBJECTS REPRESENTED IN IMAGES: FUNDAMENTALS, METHODS AND APPLICATIONS, 2007, : 261 - 266
  • [38] Research on Vehicles Information Extraction of the Shaded Area from High-Resolution Satellite Images
    Guo Dudu
    Liang Yanping
    Wang Bing
    2012 FIFTH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID 2012), VOL 1, 2012, : 477 - 480
  • [39] Lane-Level Road Extraction from High-Resolution Optical Satellite Images
    Dai, Jiguang
    Zhu, Tingting
    Zhang, Yilei
    Ma, Rongchen
    Li, Wantong
    REMOTE SENSING, 2019, 11 (22)
  • [40] River Extraction from High Resolution Satellite Images
    Khurshid, M. Hasnat
    Khan, Muhammad Faisal
    2012 5TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), 2012, : 697 - 700