• DocumentCode
    143484
  • Title

    Unmixing polarimetric radar images based on land cover type before target decomposition

  • Author

    Giordano, Sebastien ; Mercier, Gregoire ; Rudant, Jean-Paul

  • Author_Institution
    DIAS, Univ. Paris Est, Marne la Vallée, France
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    2790
  • Lastpage
    2793
  • Abstract
    A new method for unmixing radar polarimetric images with optical images is proposed. It was found that the polarimetric covariance matrix can be unmixed considering a linear model. As a result, this model is used to produce unmixed covariance matrices based on land cover types. We hope to prove that this unmixing of the polarimetric information produce greater information for land cover classification.
  • Keywords
    covariance matrices; image classification; land cover; optical images; radar imaging; radar polarimetry; remote sensing by radar; terrain mapping; land cover classification; land cover types; linear model; optical images; polarimetric covariance matrix; polarimetric information; radar polarimetric image unmixing; target decomposition; unmixed covariance matrices; Covariance matrices; Laser radar; Optical imaging; Optical scattering; Radar imaging; land cover; polarimetry; radar; unmixing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6947055
  • Filename
    6947055
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=143484