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Front. Inform. Technol. Electron. Eng.  2010, Vol. 11 Issue (5): 375-380    DOI: 10.1631/jzus.C0910201
    
Real-time motion deblurring algorithm with robust noise suppression
Hua-jun Feng*, Yong-pan Wang, Zhi-hai Xu, Qi Li, Hua Lei, Ju-feng Zhao
State Key Lab of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China
Real-time motion deblurring algorithm with robust noise suppression
Hua-jun Feng*, Yong-pan Wang, Zhi-hai Xu, Qi Li, Hua Lei, Ju-feng Zhao
State Key Lab of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China
 全文: PDF(467 KB)  
摘要： 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.
关键词： Motion blurring;  Motion kernel;  Gaussian distribution    
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.
Key words: Motion blurring    Motion kernel    Gaussian distribution
收稿日期: 2009-04-11 出版日期: 2010-04-28
CLC:  TP317.4  
基金资助: Project  supported  by  the  National  Natural  Science  Foundation  of China (No. 60977010), the National Basic Research Program (973) of
China  (No.  2009CB724006),  and  the  National  High-Tech  Research and Development (863) Program of China (No. 2006AA12Z107)
通讯作者: Hua-jun FENG     E-mail: fenghj@zju.edu.cn
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引用本文:

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. Front. Inform. Technol. Electron. Eng., 2010, 11(5): 375-380.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C0910201    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2010/V11/I5/375

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