• DocumentCode
    3306489
  • Title

    Geometrical features for the classification of very high resolution multispectral remote-sensing images

  • Author

    Luo, Bin ; Chanussot, Jocelyn

  • Author_Institution
    GIPSA-Lab., Grenoble Inst. of Technol., Grenoble, France
  • fYear
    2010
  • fDate
    26-29 Sept. 2010
  • Firstpage
    1045
  • Lastpage
    1048
  • Abstract
    In order to extract geometrical features from a multispectral image and derive a classification, an approach based on the topographic map of the image is proposed. For each pixel, the most significant structure containing it is extracted. The classification of this pixel is based on its spectral information and the geometrical features of the corresponding structure (its area and perimeter). The results obtained on multispectral remote sensing images taken by two different sensors show the efficiency of the extracted geometrical features for separating some classes with very similar spectral attributes but of different semantic meanings.
  • Keywords
    computational geometry; feature extraction; image classification; image resolution; geometrical feature extraction; high resolution multispectral remote sensing image; image classification; pixel; spectral information; topographic map; Accuracy; Buildings; Feature extraction; Pixel; Remote sensing; Roads; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2010 17th IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-7992-4
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2010.5649890
  • Filename
    5649890