DocumentCode :
3209452
Title :
Wavelet Image Restoration and Regularization Parameters Selection
Author :
Qu, Leming
Author_Institution :
Dept. of Math., Boise State Univ., Boise, ID, USA
fYear :
2009
fDate :
17-19 Dec. 2009
Firstpage :
241
Lastpage :
247
Abstract :
For the restoration of an image based on its noisy distorted observations, we propose wavelet domain restoration by scale-dependent ¿1 penalized regularization method (WaveRSL1). The data adaptive choice of the regularization parameters is based on the Akaike Information Criterion (AIC) and the degrees of freedom (df) is estimated by the number of nonzero elements in the solution. Experiments on some commonly used testing images illustrate that the proposed method possesses good empirical properties.
Keywords :
image restoration; wavelet transforms; Akaike information criterion; image deblurring; regularization parameters selection; scale-dependent ¿1 penalized regularization method; wavelet image restoration; Bayesian methods; Computer science; Fast Fourier transforms; Image restoration; Inverse problems; Mathematics; Noise reduction; Testing; Wavelet domain; Wavelet transforms; AIC; Lasso; Wavelet; image restoration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontier of Computer Science and Technology, 2009. FCST '09. Fourth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3932-4
Electronic_ISBN :
978-1-4244-5467-9
Type :
conf
DOI :
10.1109/FCST.2009.18
Filename :
5392910
Link To Document :
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