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Please use this identifier to cite or link to this item: http://idr.iitbbs.ac.in/jspui/handle/2008/617
Title: De-noising of SAR images based on Wavelet-Contourlet domain and PCA
Authors: Fang J.
Wang D.
Xiao Y.
Saikrishna D.A.
Keywords: Contourlet
Principal component analysis
SAR image de-noising
Wavelet-contourlet
Issue Date: 2014
Citation: 2
Abstract: After analyzing the speckle model of SAR, a SAR image de-noising method based on Wavelet-Contourlet transform and principal component analysis is presented. Compared with Wavelet transform and Contourlet transform, Wavelet-Contourlet transform can express images more sparsely and obtain image structure better. Most of the existing methods for image de-noising rely on accurate estimation of noise variance. However, the estimation of noise variance is very difficult in Wavelet-Contourlet domain. Propose a new method for SAR image de-noising based on Wavelet-Contourlet transform and principal component analysis. Simulation results also corroborate that the proposed algorithm is efficient and performs significantly better in reducing the speckle noise, obtaining a higher peak signal-to-noise ratio, retaining the image details, and improving the visual effect. � 2014 IEEE.
URI: http://dx.doi.org/1109/ICOSP.2014.7015143
http://10.10.32.48:8080/jspui/handle/2008/617
Appears in Collections:Research Publications

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