title: A recursive filter for despeckling SAR images.
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.
authors.forename: G R K S
authors.initials: GR
authors.lastname: Subrahmanyam
authors.forename: A N
authors.initials: AN
authors.lastname: Rajagopalan
authors.forename: R
authors.initials: R
authors.lastname: Aravind
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D011825:Radar; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity