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Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which will degrade the human interpretation and computer-aided scene analysis. In this paper, we propose a novel Bayesian multiscale method for SAR image despeckling in the non-homomorphic framework. To address the multiplicative nature, we first make the speckle contribution additive by a linear decomposition...
In this paper, a non-homomorphic wavelet-based maximum a posteriori (MAP) despeckling of SAR images using two-sided generalized Gamma distribution (GΓD) is proposed to suppress speckle. Instead of the logarithmic transformation, the multiplicative speckle model is decomposed into an additive model with signal-dependent noise. And a locally adaptive MAP estimator of noise-free wavelet coefficient is...
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