• DocumentCode
    692807
  • Title

    A sparsity promoting bilinear unmixing model

  • Author

    Gader, Paul ; Dranishnikov, Dmitri ; Zare, Alina ; Chanussot, Jocelyn

  • Author_Institution
    Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
  • fYear
    2012
  • fDate
    4-7 June 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    An algorithm, Bilinear SPICE (BISPICE), for simultaneously estimating the number of endmembers, the endmembers, and proportions for a bilinear mixing model is derived and evaluated. BISPICE generalizes the SPICE algorithm for linear mixing. The proportion estimation steps of SPICE and BISPICE are similar. However, the endmember updates, one novel aspect of the work, are quite different. The SPICE objective function is quadratic in the endmembers. The BISPICE is a fourth degree polynomial. In SPICE, endmembers are updated simultaneously via a closed form. In BISPICE, each endmember must be updated with respect to all other endmembers. Empirically, BISPICE estimated endmembers and proportions more accurately then SPICE, even though the data fitting error was higher.
  • Keywords
    geophysical image processing; hyperspectral imaging; BISPICE algorithm; SPICE objective function; bilinear SPICE algorithm; data fitting error; endmember estimation; fourth degree polynomial; linear mixing; sparsity promoting bilinear unmixing model; Computational modeling; Hyperspectral imaging; Ice; Linear programming; SPICE; Signal processing; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2012 4th Workshop on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4799-3405-8
  • Type

    conf

  • DOI
    10.1109/WHISPERS.2012.6874255
  • Filename
    6874255