Despeckling of TerraSAR-X Data Using Second-Generation Wavelets

This letter presents the despeckling of synthetic aperture radar (SAR) images within the bandelet and contourlet domains. A model-based approach is presented for the despeckling of SAR images. The speckle-reduced estimate is found using the first-order Bayesian inference, and the best model's p...

Full description

Saved in:
Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2010-01, Vol.7 (1), p.68-72
Main Authors: Gleich, D., Kseneman, M., Datcu, M.
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Bayesian inference
Bayesian methods
Filters
Inference
Inference algorithms
Layout
Mathematical models
Parameter estimation
Shape
Signal processing algorithms
Speckle
speckle reduction
Synthetic aperture radar
synthetic aperture radar (SAR)
Transforms
Wavelet domain
wavelet transform
Wavelet transforms
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This letter presents the despeckling of synthetic aperture radar (SAR) images within the bandelet and contourlet domains. A model-based approach is presented for the despeckling of SAR images. The speckle-reduced estimate is found using the first-order Bayesian inference, and the best model's parameters are estimated using the second-order Bayesian inference. Synthetic and real images are used for evaluating the qualities of the despeckling methods. The experimental results showed that the combination of Bayesian inference and bandelet transform outperforms the contourlet-based despeckling algorithm using synthetic data and objective measurements.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2009.2020610