Title :
A Recursive Filter for Despeckling SAR Images
Author :
Subrahmanyam, G.R.K.S. ; Rajagopalan, A.N. ; Aravind, R.
Author_Institution :
Dept. of Electr. Eng., IIT Madras, Chennai
Abstract :
This correspondence proposes a recursive algorithm for noise reduction in synthetic aperture radar imagery. Excellent despeckling in conjunction with feature preservation is achieved by incorporating a discontinuity-adaptive Markov random field prior within the unscented Kalman filter framework through importance sampling. The performance of this method is demonstrated on both synthetic and real examples.
Keywords :
Kalman filters; Markov processes; image sampling; radar imaging; recursive filters; synthetic aperture radar; SAR images; discontinuity-adaptive Markov random; feature preservation; noise reduction; recursive filter; synthetic aperture radar; unscented Kalman filter; Adaptive filters; Degradation; Image resolution; Image texture; Markov random fields; Noise reduction; Nonlinear filters; Speckle; Synthetic aperture radar; Wavelet coefficients; Importance sampling; Markov random field (MRF); speckle; synthetic aperture radar (SAR); unscented Kalman filter (UKF); Algorithms; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Radar; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2008.2002160
