• DocumentCode
    3348779
  • Title

    An entropy based classification scheme for polarimetric SAR data

  • Author

    Cloude, S.R.

  • Author_Institution
    IRESTE, Nantes Univ., France
  • Volume
    3
  • fYear
    34881
  • fDate
    10-14 Jul1995
  • Firstpage
    2000
  • Abstract
    Considers a new unsupervised classification scheme for polarimetric SAR data. This scheme makes use of a local estimate of the scattering entropy in the scene to determine the number of discernible classes in the data. Examples are presented of application of the scheme to AIRSAR data provided by NASA/JPL
  • Keywords
    electromagnetic wave scattering; entropy; geophysical signal processing; image classification; polarimetry; radar cross-sections; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; unsupervised learning; AIRSAR data; discernible classes; entropy based classification scheme; polarimetric SAR data; scattering entropy; scene; unsupervised classification scheme; Additive noise; Eigenvalues and eigenfunctions; Entropy; Equations; Image analysis; Layout; Radar imaging; Radar scattering; Scattering parameters; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
  • Conference_Location
    Firenze
  • Print_ISBN
    0-7803-2567-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.1995.524090
  • Filename
    524090