|Blur-Kernel Bound Estimation From Pyramid Statistics|
|Shaoguo Liu; Haibo Wang; Jue Wang; Chunhong Pan
|Source Publication||IEEE Transactions on Circuits and Systems for Video Technology
|Volume||26Issue:5Pages:1012 - 1016|
|Abstract||This letter presents an approach for automatically estimating the spatial bound of the blur kernel in a motion-blurred image based on the statistics of multilevel image gradients. We observe that blur has a significant impact on the histogram of oriented gradients (HOGs) at higher levels of an image pyramid, but has much less of an impact at coarser levels. Based on this fact, we estimate the spatial bound of the unknown blur kernel using a learning-based approach. We first learn a generic pyramid HOG model from natural sharp images, then given an HOG pyramid of a blurry image, we predict the corresponding model of its latent sharp image. Finally, we learn another model to predict the spatial kernel bound from the difference between the observed and the predicted HOG pyramids. Experimental results show that the proposed method can estimate accurate blur kernel sizes, enabling existing blind deconvolution methods to achieve best possible results.|
|Keyword||Blur-kernel Bound Estimation
|Affiliation||National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences|
Shaoguo Liu,Haibo Wang,Jue Wang,et al. Blur-Kernel Bound Estimation From Pyramid Statistics[J]. IEEE Transactions on Circuits and Systems for Video Technology,2016,26(5):1012 - 1016.
Shaoguo Liu,Haibo Wang,Jue Wang,&Chunhong Pan.(2016).Blur-Kernel Bound Estimation From Pyramid Statistics.IEEE Transactions on Circuits and Systems for Video Technology,26(5),1012 - 1016.
Shaoguo Liu,et al."Blur-Kernel Bound Estimation From Pyramid Statistics".IEEE Transactions on Circuits and Systems for Video Technology 26.5(2016):1012 - 1016.
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