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
Link To Document :
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