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