• DocumentCode
    1327744
  • Title

    Two-dimensional adaptive block Kalman filtering of SAR imagery

  • Author

    Azimi-Sadjadi, Mahmood R. ; Bannour, Sami

  • Author_Institution
    Dept. of Electr. Eng., Colorado State Univ., Fort Collins, CO, USA
  • Volume
    29
  • Issue
    5
  • fYear
    1991
  • fDate
    9/1/1991 12:00:00 AM
  • Firstpage
    742
  • Lastpage
    753
  • Abstract
    A method for removing speckle from synthetic aperture radar (SAR) imagery by using 2-D adaptive block Kalman filtering is introduced. The image process is represented by an autoregressive model with a nonsymmetric half-plane (NSHP) region of support. New 2-D Kalman filtering equations are derived which taken into account not only the effect of speckles as multiplicative noise but also the effects of the additive receiver thermal noise and the blur. This method assumes local stationarity within a processing window, whereas the image can be assumed to be globally nonstationary. A recursive identification process using the stochastic Newton approach is also proposed which can be used on-line to estimate the filter parameters based upon the information within each new block of the image. Simulation results on several images are provided to indicate the effectiveness of the proposed method when used to remove the effects of speckle noise as well as those of the additive noise
  • Keywords
    Kalman filters; adaptive filters; computerised picture processing; filtering and prediction theory; geophysics computing; random noise; remote sensing by radar; speckle; 2D filtering; SAR imagery; adaptive block Kalman filtering; additive receiver thermal noise; autoregressive model; blur; multiplicative noise; nonsymmetric half-plane; recursive identification process; remote sensing; speckle; stochastic Newton approach; Adaptive filters; Additive noise; Equations; Filtering; Kalman filters; Parameter estimation; Recursive estimation; Speckle; Stochastic resonance; Synthetic aperture radar;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.83989
  • Filename
    83989