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CLC number: TP317.4

On-line Access: 2010-04-28

Received: 2009-04-11

Revision Accepted: 2009-09-29

Crosschecked: 2010-03-29

Cited: 2

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.5 P.375-380

10.1631/jzus.C0910201


Real-time motion deblurring algorithm with robust noise suppression


Author(s):  Hua-jun Feng, Yong-pan Wang, Zhi-hai Xu, Qi Li, Hua Lei, Ju-feng Zhao

Affiliation(s):  State Key Lab of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   fenghj@zju.edu.cn

Key Words:  Motion blurring, Motion kernel, Gaussian distribution


Hua-jun Feng, Yong-pan Wang, Zhi-hai Xu, Qi Li, Hua Lei, Ju-feng Zhao. Real-time motion deblurring algorithm with robust noise suppression[J]. Journal of Zhejiang University Science C, 2010, 11(5): 375-380.

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author="Hua-jun Feng, Yong-pan Wang, Zhi-hai Xu, Qi Li, Hua Lei, Ju-feng Zhao",
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doi="10.1631/jzus.C0910201"
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%A Yong-pan Wang
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%A Qi Li
%A Hua Lei
%A Ju-feng Zhao
%J Journal of Zhejiang University SCIENCE C
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%@ 1869-1951
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910201

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T1 - Real-time motion deblurring algorithm with robust noise suppression
A1 - Hua-jun Feng
A1 - Yong-pan Wang
A1 - Zhi-hai Xu
A1 - Qi Li
A1 - Hua Lei
A1 - Ju-feng Zhao
J0 - Journal of Zhejiang University Science C
VL - 11
IS - 5
SP - 375
EP - 380
%@ 1869-1951
Y1 - 2010
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C0910201


Abstract: 
In an image restoration process, to obtain good results is challenging because of the unavoidable existence of noise even if the blurring information is already known. To suppress the deterioration caused by noise during the image deblurring process, we propose a new deblurring method with a known kernel. First, the noise in the measurement process is assumed to meet the gaussian distribution to fit the natural noise distribution. Second, the first and second orders of derivatives are supposed to satisfy the independent gaussian distribution to control the non-uniform noise. Experimental results show that our method is obviously superior to the Wiener filter, regularized filter, and Richardson-Lucy (RL) algorithm. Moreover, owing to processing in the frequency domain, it runs faster than the other algorithms, in particular about six times faster than the RL algorithm.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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