Blur-Kernel Bound Estimation From Pyramid Statistics

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Blur-Kernel Bound Estimation From Pyramid Statistics
	Shaoguo Liu; Haibo Wang; Jue Wang; Chunhong Pan
发表期刊	IEEE Transactions on Circuits and Systems for Video Technology
	2016-05
卷号	26 期号:5 页码:1012 - 1016
摘要	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.
关键词	Blur-kernel Bound Estimation Image Deblur Motion Deblur Motion Prior Pyramid Statistics
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/20367
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
作者单位	National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	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.
APA	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.
MLA	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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