TY - GEN
T1 - Robust multiframe blind image deblurring
AU - Haichao, Zhang
AU - Yanning, Zhang
PY - 2009
Y1 - 2009
N2 - Multiframe deblurring estimates a sharp and clear image from a set of blurry and noisy observations. A variety of deblurring methods are proposed in the past two decades. However, most of them are sensitive to their assumed data and noise model, limiting their utility. This paper first reviews the related works and shows the non-robustness in the traditional model and then proposes a robust Bayesian multiframe blind deblurring model. Alternating minimization scheme is adopted to solve this model. Experimental results indicate the effectiveness of the proposed method.
AB - Multiframe deblurring estimates a sharp and clear image from a set of blurry and noisy observations. A variety of deblurring methods are proposed in the past two decades. However, most of them are sensitive to their assumed data and noise model, limiting their utility. This paper first reviews the related works and shows the non-robustness in the traditional model and then proposes a robust Bayesian multiframe blind deblurring model. Alternating minimization scheme is adopted to solve this model. Experimental results indicate the effectiveness of the proposed method.
UR - https://www.scopus.com/pages/publications/73849083621
U2 - 10.1109/CISP.2009.5304209
DO - 10.1109/CISP.2009.5304209
M3 - 会议稿件
AN - SCOPUS:73849083621
SN - 9781424441310
T3 - Proceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09
BT - Proceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09
T2 - 2009 2nd International Congress on Image and Signal Processing, CISP'09
Y2 - 17 October 2009 through 19 October 2009
ER -