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A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage

Sara ParrilliDepartment of Biomedical, Electronic, and Telecommunication Engineering, University of Naples Federico II, Naples, ItalyMariana PodericoDepartment of Biomedical, Electronic, and Telecommunication Engineering, University of Naples Federico II, Naples, ItalyCesario Vincenzo AngelinoDepartment of Biomedical, Electronic, and Telecommunication Engineering, University of Naples Federico II, Naples, ItalyLuisa VerdolivaDepartment of Biomedical, Electronic, and Telecommunication Engineering, University of Naples Federico II, Naples, Italy

2011en

ABI

Annotatsiya

We propose a novel despeckling algorithm for synthetic aperture radar (SAR) images based on the concepts of nonlocal filtering and wavelet-domain shrinkage. It follows the structure of the block-matching 3-D algorithm, recently proposed for additive white Gaussian noise denoising, but modifies its major processing steps in order to take into account the peculiarities of SAR images. A probabilistic similarity measure is used for the block-matching step, while the wavelet shrinkage is developed using an additive signal-dependent noise model and looking for the optimum local linear minimum-mean-square-error estimator in the wavelet domain. The proposed technique compares favorably w.r.t. several state-of-the-art reference techniques, with better results both in terms of signal-to-noise ratio (on simulated speckled images) and of perceived image quality.

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Identifikatorlar

DOI: 10.1109/tgrs.2011.2161586

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