• DocumentCode
    3071197
  • Title

    Independent Component Analysis within polarimetric incoherent target decomposition

  • Author

    Besic, Nikola ; Vasile, G. ; Chanussot, Jocelyn ; Stankovic, Stevan ; Boldo, Didier ; D´Urso, Guy

  • Author_Institution
    GIPSA-Lab., Grenoble Inst. of Technol., Grenoble, France
  • fYear
    2013
  • fDate
    21-26 July 2013
  • Firstpage
    4158
  • Lastpage
    4161
  • Abstract
    This paper represents a part of our efforts to generalize polarimetric incoherent target decomposition to the level of BSS techniques by introducing the ICA method instead of the conventional eigenvector decomposition. We compare, in the frame of polarimetric incoherent target decomposition, several criteria for the estimation of complex independent components [1, 2]. This is done by parametrising the obtained dominant and mutually independent target vectors using the TSVM [3] and representing them on the corresponding Poincaré sphere. We demonstrate notably good performances of the proposed method applied on the RAMSES POLSAR X-band image, by precisely identifying the class of trihedral reflectors present in the scene. Logarithm and square root nonlinearities - two of the three proposed criteria for complex IC derivation prove to be very efficient. The best discrimination between the a priori defined classes appears to be achieved with the principal kurtosis criterion. Finally, the algorithm using the former two functions leads to very interesting entropy estimation.
  • Keywords
    blind source separation; geophysical image processing; independent component analysis; radar polarimetry; remote sensing by radar; synthetic aperture radar; Poincare sphere; RAMSES POLSAR X-band image; blind source separation technique; entropy estimation; independent component analysis; logarithm nonlinearities; polarimetric incoherent target decomposition; principal kurtosis criterion; square root nonlinearities; target scattering vector model; trihedral reflectors; Entropy; Estimation; Independent component analysis; Matrix decomposition; Principal component analysis; Scattering; Vectors; Complex Fast-ICA; Poincaré sphere; Polarimetric ICTD; TVSM; non-gaussianity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
  • Conference_Location
    Melbourne, VIC
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4799-1114-1
  • Type

    conf

  • DOI
    10.1109/IGARSS.2013.6723749
  • Filename
    6723749