TY - GEN
T1 - Joint motion deblurring with blurred/noisy image pair
AU - Li, Haisen
AU - Zhang, Yanning
AU - Sun, Jinqiu
AU - Gong, Dong
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/4
Y1 - 2014/12/4
N2 - Motion blurred images are widely existing when using a hand-held camera especially under the dim lighting conditions. Since edge information contained in the noisy image may be blurred by the motion blur, a blurred/noisy image pair captured under different exposure time can help to restore a sharp image. In the traditional deblurring methods based on blurred/noisy image pair, the deblurring process is in series with the denoising process, so that restoration result is sensitive to the denoised result. In this paper, we propose a robust algorithm to obtain the sharp image by fusing the blurred image and noisy image. By joint modeling the deblurring model and denoising model, the restoration result can be optimized via estimating the sharp image and blur kernel alternately in the proposed methods, and it is not sensitive to the denoised result benefited by the joint model. Experimental results demonstrated that the proposed method can achieve better performance compared with the state-of-the-art single image denoising methods, single image deblurring methods and blurred/noisy pair deblurring methods.
AB - Motion blurred images are widely existing when using a hand-held camera especially under the dim lighting conditions. Since edge information contained in the noisy image may be blurred by the motion blur, a blurred/noisy image pair captured under different exposure time can help to restore a sharp image. In the traditional deblurring methods based on blurred/noisy image pair, the deblurring process is in series with the denoising process, so that restoration result is sensitive to the denoised result. In this paper, we propose a robust algorithm to obtain the sharp image by fusing the blurred image and noisy image. By joint modeling the deblurring model and denoising model, the restoration result can be optimized via estimating the sharp image and blur kernel alternately in the proposed methods, and it is not sensitive to the denoised result benefited by the joint model. Experimental results demonstrated that the proposed method can achieve better performance compared with the state-of-the-art single image denoising methods, single image deblurring methods and blurred/noisy pair deblurring methods.
UR - http://www.scopus.com/inward/record.url?scp=84919922579&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2014.185
DO - 10.1109/ICPR.2014.185
M3 - 会议稿件
AN - SCOPUS:84919922579
T3 - Proceedings - International Conference on Pattern Recognition
SP - 1020
EP - 1024
BT - Proceedings - International Conference on Pattern Recognition
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference on Pattern Recognition, ICPR 2014
Y2 - 24 August 2014 through 28 August 2014
ER -