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
  • [21] Roads extraction through texture from aerial and high-resolution satellite images
    Malpica, JA
    Pedraza, J
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING VI, 2001, 4170 : 358 - 366
  • [22] Automated extraction of road network from medium-and high-resolution images
    Dal Poz A.P.
    Zanin R.B.
    Do Vale G.M.
    Pattern Recognition and Image Analysis, 2006, 16 (2) : 239 - 248
  • [23] ESFNet: Efficient Network for Building Extraction From High-Resolution Aerial images
    Lin, Jingbo
    Jing, Weipeng
    Song, Houbing
    Chen, Guangsheng
    IEEE ACCESS, 2019, 7 : 54285 - 54294
  • [24] Deep Learning for Building Extraction from High-Resolution Remote Sensing Images
    Norelyaqine, Abderrahim
    Saadane, Abderrahim
    ADVANCED TECHNOLOGIES FOR HUMANITY, 2022, 110 : 116 - 128
  • [25] Automatic Building Detection with Polygonizing and Attribute Extraction from High-Resolution Images
    Daranagama, Samitha
    Witayangkurn, Apichon
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2021, 10 (09)
  • [26] Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information
    Xiaoying Jin
    Curt H. Davis
    EURASIP Journal on Advances in Signal Processing, 2005
  • [27] Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information
    Jin, XY
    Davis, CH
    EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING, 2005, 2005 (14) : 2196 - 2206
  • [28] Building extraction from high-resolution satellite images in urban areas: recent methods and strategies against significant challenges
    Ghanea, Mohsen
    Moallem, Payman
    Momeni, Mehdi
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2016, 37 (21) : 5234 - 5248
  • [29] Fully automated road network extraction from high-resolution satellite multispectral imagery
    Shackelford, AK
    Davis, CH
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 461 - 463
  • [30] Automated interpretation of protective forest plantings on high-resolution satellite images
    K. N. Kulik
    O. Yu. Kosheleva
    Russian Agricultural Sciences, 2011, 37 (3) : 265 - 267