DocumentCode
1940526
Title
Image Deblurring Regularized by Wavelet Probability Shrink
Author
Wang Zhiming
Author_Institution
Sch. of Comput. & Commun. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
fYear
2011
fDate
5-7 Aug. 2011
Firstpage
610
Lastpage
613
Abstract
An image deblurring algorithm based on wavelet probability shrink regularization is proposed. Denoise and deblur were alternatively executed by least square approximate and probability shrinkage. After several iterations of deblur, probability shrink based on stationary wavelet transform (SWT) were used once for denoising. Experimental results show that proposed algorithm obtained better results on several benchmark images than classical regularization techniques such as wavelet soft shrink, TV, or even non-local TV proposed more recently.
Keywords
image restoration; least squares approximations; probability; wavelet transforms; image deblurring; least square approximation; probability shrinkage; stationary wavelet transform; wavelet probability shrink regularization; Image restoration; PSNR; TV; Wavelet domain; Wavelet transforms; Image Deblurring; ProbabiLity Shrink; Stationary Wavelet Transform (SWT); Wavelet Shrink;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Manufacturing and Automation (ICDMA), 2011 Second International Conference on
Conference_Location
Zhangjiajie, Hunan
Print_ISBN
978-1-4577-0755-1
Electronic_ISBN
978-0-7695-4455-7
Type
conf
DOI
10.1109/ICDMA.2011.152
Filename
6051921
Link To Document