DocumentCode
2942552
Title
Image Deblurring with Impulse Noise Using Split Bregman Algorithm
Author
Liya, Yi ; Xiaolei, Lu ; Jinjun, Wang ; Benxiong, Huang
Author_Institution
Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume
2
fYear
2009
fDate
12-14 Dec. 2009
Firstpage
233
Lastpage
238
Abstract
We propose an effective method to resolve blurred images with impulse noise. Our method has two steps. First, an improved adaptive median filter is proposed for image denoising; And second, the problem of deblurring the denoised image is formulated as to minimize the object function which consists of L1 data-fedility term and double regularization term. The minimization problem is solved by split Bregman algorithm. Numerical results using image with different blurs and impulse noise show that the proposed method gives better performance than the variable splitting alternative minimization algorithm in by objective peak signal to noise ratio and subjective vision quality, which demonstrates the efficiency of our proposed algorithms.
Keywords
adaptive filters; image denoising; impulse noise; median filters; L1 data-fedility term; double regularization term; image deblurring; image denoising; improved adaptive median filter; impulse noise; object function minimization; objective peak signal to noise ratio; split Bregman algorithm; subjective vision quality; variable splitting alternative minimization algorithm; Adaptive filters; Algorithm design and analysis; Computational intelligence; Filtering algorithms; Gaussian noise; Image denoising; Image restoration; Minimization methods; Noise reduction; PSNR; double regularization; image deblurring; impulse noise; split Bregman algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location
Changsha
Print_ISBN
978-0-7695-3865-5
Type
conf
DOI
10.1109/ISCID.2009.205
Filename
5371081
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