• DocumentCode
    2915200
  • Title

    ICE: an automated statistical approach to identifying endmembers in hyperspectral images

  • Author

    Berman, Mark ; Kiiveri, Harri ; Langerstrom, R. ; Ernst, Andreas ; Dunne, Rob ; Huntington, Jon

  • Author_Institution
    CSIRO Math. & Inf. Sci., Macquarie Univ. Campus, North Ryde, NSW, Australia
  • Volume
    1
  • fYear
    2003
  • fDate
    21-25 July 2003
  • Firstpage
    279
  • Abstract
    Several of the more important endmember-finding algorithms for hyperspectral data are discussed and their shortcomings highlighted. A new algorithm, ICE, which attempts to overcome these shortcomings is introduced. An example of is use is given.
  • Keywords
    geophysical signal processing; geophysical techniques; image processing; spectral analysis; ICE; automated statistical approach; endmember-finding algorithms; endmembers identification; hyperspectral data; hyperspectral images; iterated constrained endmembers; Australia; Hyperspectral imaging; Ice; Layout; Noise shaping; Packaging; Pixel; Reflectivity; Solid modeling; Spectral shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
  • Print_ISBN
    0-7803-7929-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2003.1293750
  • Filename
    1293750