Title :
Edge-preserving unscented Kalman filter for speckle reduction
Author :
Subrahmanyam, G.R.K. ; Rajagopalan, A.N. ; Aravind, R. ; Rigoll, Gerhard
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol. Madras, Chennai
Abstract :
We propose a recursive spatial-domain speckle reduction algorithm for synthetic aperture radar (SAR) imagery based on the unscented Kalman filter (UKF) with a discontinuity-adaptive Markov random field (DAMRF) prior. The capability of the UKF in handling speckle noise and the feature preservation ability of the DAMRF model are explored within a unified framework through importance sampling.
Keywords :
Kalman filters; Markov processes; edge detection; importance sampling; radar imaging; synthetic aperture radar; discontinuity-adaptive Markov random field; edge-preserving unscented Kalman filter; feature preservation ability; importance sampling; speckle noise handling; speckle reduction; synthetic aperture radar imagery; Adaptive filters; Degradation; Image texture; Markov random fields; Monte Carlo methods; Nonlinear filters; Random variables; Speckle; Statistics; Wavelet domain;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761408
