A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image processing and data analysis: the multiscale approach
Image processing and data analysis: the multiscale approach
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Fast estimation of the parameters of alpha-stable impulsiveinterference
IEEE Transactions on Signal Processing
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
Image enhancement based on a nonlinear multiscale method
IEEE Transactions on Image Processing
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
A novel wavelet domain statistical approach for denoising SAR images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Statistical modeling and denoising Wigner-Ville distribution
Digital Signal Processing
Radar detection algorithm for GARCH clutter model
Digital Signal Processing
Amplitude vs intensity Bayesian despeckling in the wavelet domain for SAR images
Digital Signal Processing
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A novel Bayesian-based speckle suppression method for Synthetic Aperture Radar (SAR) images is presented that preserves the structural features and textural information of the scene. First, the logarithmic transform of the original image is analyzed into the multiscale wavelet domain. We show that the wavelet coefficients of SAR images have significantly non-Gaussian statistics that are best described by the 2-D GARCH model. By using the 2-D GARCH model on the wavelet coefficients, we are capable of taking into account important characteristics of wavelet coefficients, such as heavy tailed marginal distribution and the dependencies between the coefficients. Furthermore, we use a maximum a posteriori (MAP) estimator for estimating the clean image wavelet coefficients. Finally, we compare our proposed method with various speckle suppression methods applied on synthetic and actual SAR images and we verify the performance improvement in utilizing the new strategy.