• DocumentCode
    2903529
  • Title

    Extraction and selection of robust features for classification of multispectral remote-sensing images

  • Author

    Bruzzone, Lorenzo ; Prieto, Diego Fernández ; Silvano, Giovanni

  • Author_Institution
    Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    119
  • Abstract
    In this paper, we present an approach to the extraction and selection of robust features for classification of multispectral remote-sensing images. In particular, several robust features are proposed that, given a specific land-cover class, aim to exhibit an invariant behavior versus variations in the acquisition conditions of the images considered. In addition, a technique is presented, which is able to adaptively select the most robust features for a given problem
  • Keywords
    feature extraction; geophysical signal processing; image classification; remote sensing; acquisition conditions; classification; extraction; invariant behavior; land-cover; multispectral remote-sensing images; robust features; selection; Absorption; Electronic mail; Feature extraction; Pixel; Reflectivity; Remote sensing; Robustness; Sensor phenomena and characterization; Shape measurement; Soil moisture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
  • Conference_Location
    Hamburg
  • Print_ISBN
    0-7803-5207-6
  • Type

    conf

  • DOI
    10.1109/IGARSS.1999.773420
  • Filename
    773420