DocumentCode
2084856
Title
Despeckling SAR Images Using Bayes-Shrink in Bandelet Domain
Author
Xu, Yanan ; Gao, Qingwei ; Lu, Yixiang ; Zhong, Weinian
Author_Institution
Key Lab. of Intell. Comput. & Signal Process., Anhui Univ., Hefei, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
4
Abstract
Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of scattering phenomena. This paper presents a despeckling method for SAR images based on adaptive bandelets thresholding. This threshold is derived in a Bayesian framework. The proposed threshold is simple and closed form, and it is applied to adaptive bandelets coefficients to achieve more satisfying results. The performances of adaptive bandelets Bayes-shrink soft-thresholding and wavelet thresholding for despeckling SAR images are compared through an experiment. Experiment results clearly demonstrated the capability of the proposed scheme in SAR image speckle reduction especially for SAR images possessing detailed textures.
Keywords
electromagnetic wave scattering; image denoising; image segmentation; image texture; radar imaging; synthetic aperture radar; wavelet transforms; Bayes-shrink soft-thresholding; Bayesian framework; SAR image despeckling method; adaptive bandelet thresholding; image denoising; image texture; scattering phenomena; synthetic aperture radar; wavelet thresholding; Discrete wavelet transforms; Educational technology; Geometry; Laboratories; Noise reduction; Radar scattering; Radar signal processing; Speckle; Synthetic aperture radar; Wavelet domain;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4129-7
Electronic_ISBN
978-1-4244-4131-0
Type
conf
DOI
10.1109/CISP.2009.5301474
Filename
5301474
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