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
Link To Document :
بازگشت