DocumentCode :
508887
Title :
A Novel SAR Images Restoration Using Multiscale SVR
Author :
Cheng, Hui ; Han, Hai
Author_Institution :
Sch. of Math. & Comput. Sci., Jianghan Univ., Wuhan, China
Volume :
1
fYear :
2009
fDate :
18-20 Nov. 2009
Firstpage :
230
Lastpage :
233
Abstract :
Synthetic aperture radar (SAR) has become one of the most powerful observation tools in the studies of natural environments and Earth resources. However the granular appearance of speckle noise in synthetic aperture radar imagery makes it very difficult to visually and automatically interpret information of SAR data. In this paper, according to the inherent speckle property of SAR image, we proposed a multiscale restoration algorithm by fusing the wavelet coefficients manipulation technique with support vector regression. The kernel parameter was used respectively in the different scale. For preserving sharp edges information, in our algorithm the shrinkage strategy is to compare the estimated value with the original coefficient value of that pixel using the absolute deviation of them. We define a rule for modifying wavelet coefficients based on support vector regression (SVR). Real SAR images are used to evaluate the restoration performance of our proposed algorithm along with another wavelet-based restoration algorithm, as well as the Lee speckle filter. Experimental results show that the proposed method outperforms standard wavelet restoration techniques.
Keywords :
filtering theory; image restoration; regression analysis; speckle; synthetic aperture radar; wavelet transforms; Earth resources; Lee speckle filter; SAR images restoration; multiscale SVR; multiscale restoration algorithm; sharp edges information; speckle property; support vector regression; synthetic aperture radar; wavelet coefficients manipulation technique; wavelet restoration techniques; wavelet-based restoration algorithm; Additive white noise; Filters; Gaussian noise; Image processing; Image restoration; Noise reduction; Spatial resolution; Speckle; Synthetic aperture radar; Wavelet coefficients; SAR; images restoration; support vector regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Information Networking and Security, 2009. MINES '09. International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-0-7695-3843-3
Electronic_ISBN :
978-1-4244-5068-8
Type :
conf
DOI :
10.1109/MINES.2009.255
Filename :
5368361
Link To Document :
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