DocumentCode
535178
Title
Despeckling SAR image using nonsubsampled directionlets combining with GSM model
Author
Gao, Qingwei ; Zhang, Chi ; Lu, Yixiang
Author_Institution
Key Lab. of Optio-Electron. Inf. Acquisition & Manipulation, Anhui Univ., Hefei, China
Volume
2
fYear
2010
fDate
16-18 Oct. 2010
Firstpage
664
Lastpage
667
Abstract
As speckle noise suppression is important for Synthetic aperture radar (SAR) images processing, this paper presents an approach for SAR image despeckling based on nonsubsampled directionlets. Firstly, images are partitioned into subbands using nonsubsampled directionlets. Then, the coefficients of subbands are modeled with Gaussian scale mixtures (GSM). Besides, for reducing the speckle noise, coefficients are estimated by Bayes least square estimation. Lastly, to evaluate the performance of this despeckling method, four performance evaluation parameters are used. Experimental results show that this method performs better in comparison with the spatial filter and standard wavelet transform not only in speckle suppression, but also in detail preservation.
Keywords
Bayes methods; Gaussian processes; image denoising; least squares approximations; radar imaging; synthetic aperture radar; wavelet transforms; Bayes least square estimation; GSM model; Gaussian scale mixtures; SAR image despeckling; nonsubsampled directionlets; spatial filter; speckle noise suppression; synthetic aperture radar; wavelet transform; Filtering; GSM; Noise; Speckle; Synthetic aperture radar; Wavelet transforms; Gaussian scale mixtures model; SAR image; despeckling; nonsubsampled directionlet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location
Yantai
Print_ISBN
978-1-4244-6513-2
Type
conf
DOI
10.1109/CISP.2010.5647222
Filename
5647222
Link To Document