• DocumentCode
    152541
  • Title

    Endmember Detection using Enhanced Constrained Optimization in Hyperspectral Imaging

  • Author

    Yuksel, S.E.

  • Author_Institution
    Elektrik ve Elektron. Muhendisligi Bolumu, Hacettepe Univ., Ankara, Turkey
  • fYear
    2014
  • fDate
    23-25 April 2014
  • Firstpage
    1023
  • Lastpage
    1026
  • Abstract
    A new algorithm is presented for linear spectral mixture analysis that respects the constraints on the end members. The results show that it provides a more robust solution as compared to the ICE and SPICE algorithms due to the use of constrained quadratic optimization for end member detection.
  • Keywords
    hyperspectral imaging; image processing; mixture models; optimisation; constrained quadratic optimization; end member detection; enhanced constrained optimization; hyperspectral imaging; linear spectral mixture analysis; Conferences; Hyperspectral imaging; Ice; SPICE; Signal processing; Hyperspectral Image Processing; end member detection; quadratic optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2014 22nd
  • Conference_Location
    Trabzon
  • Type

    conf

  • DOI
    10.1109/SIU.2014.6830406
  • Filename
    6830406
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=152541