• DocumentCode
    1891404
  • Title

    Meta-optimization of the Extended Kalman Filter´s parameters for improved feature extraction on hyper-temporal images

  • Author

    Salmon, B.P. ; Kleynhans, W. ; van den Bergh, F. ; Olivier, J.C. ; Marais, W.J. ; Wessels, K.J.

  • Author_Institution
    Dept. of Electr., Electron. & Comput. Eng., Univ. of Pretoria, Pretoria, South Africa
  • fYear
    2011
  • fDate
    24-29 July 2011
  • Firstpage
    2543
  • Lastpage
    2546
  • Abstract
    Time series derived from the first two spectral bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance product can be modelled as a pair of triply (mean, phase and amplitude) modulated cosine functions. This paper proposes a meta-optimization approach for setting the parameters of the non-linear Extended Kalman Filter to rapidly and efficiently estimate the features for the pair of triply modulated cosine functions. The approach is based on a unsupervised search algorithm over an appropriately defined manifold using spatial and temporal information. Performance of the new method is compared to other applicable methods and is tested on the Gauteng province which is South Africa´s province with the fastest growing economy.
  • Keywords
    Kalman filters; feature extraction; geophysical image processing; geophysical techniques; image resolution; optimisation; time series; Gauteng province; Moderate-Resolution Imaging Spectroradiometer; South Africa province; feature extraction; hypertemporal image; land surface reflectance product; metaoptimization method; modulated cosine function; nonlinear extended Kalman filter; spatial information; temporal information; time series; unsupervised search algorithm; Clustering algorithms; Feature extraction; Humans; MODIS; Manifolds; Noise; Time series analysis; Hellinger distance; Kalman Filter; Spatial information; Time series analysis; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
  • Conference_Location
    Vancouver, BC
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4577-1003-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2011.6049730
  • Filename
    6049730