Conference Paper: Motion estimation method for blurred videos and application of deblurring with spatially varying blur kernels

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Publisher Website: 10.1109/ICCIT.2010.5711083
Scopus: eid_2-s2.0-79952689989

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Title	Motion estimation method for blurred videos and application of deblurring with spatially varying blur kernels
Authors	He, XC1 Luo, T1 Yuk, SC1 Chow, KP1 Wong, KYK1 Chung, RHY2
Keywords	Deblurring Motion Estimation Spatially Varing Blur Kernels
Issue Date	2010
Citation	Proceeding - 5Th International Conference On Computer Sciences And Convergence Information Technology, Iccit 2010, 2010, p. 355-359 [How to Cite?] DOI: http://dx.doi.org/10.1109/ICCIT.2010.5711083
Abstract	Optical flow methods, such as Lucas-Kanade and Horn-Schunck algorithms, are popular in motion estimation. However, they fall short on accuracy when they are applied to blurred videos. Some people utilize hybrid camera system to get a low resolution image to suppress the blurring effect so that more accurate optical flow for blurred high resolution image can be further derived, though in most of the practical environments it may not be feasible to deploy hybrid camera systems from cost perspective. In this paper, we propose a novel approach to estimate motion from a blurred video without the use of hybrid camera system, and to reduce motion blur by calculating its spatially varying blur kernels. Essentially, we first separate moving objects into small regions and use the corners of their boundaries as feature points, and then apply Hierarchical Block Matching Algorithm (HBMA) to track them between frames. Motions of non-corner pixels can therefore be estimated by interpolating the motion of these corner points, which further support the calculation of the spatially varying blur kernels for deblurring purpose. Experimental results demonstrate the effectiveness of proposed method.
DOI	http://dx.doi.org/10.1109/ICCIT.2010.5711083
References	References in Scopus

DC Field	Value
dc.contributor.author	He, XC
dc.contributor.author	Luo, T
dc.contributor.author	Yuk, SC
dc.contributor.author	Chow, KP
dc.contributor.author	Wong, KYK
dc.contributor.author	Chung, RHY
dc.date.accessioned	2012-06-26T06:32:15Z
dc.date.available	2012-06-26T06:32:15Z
dc.date.issued	2010
dc.description.abstract	Optical flow methods, such as Lucas-Kanade and Horn-Schunck algorithms, are popular in motion estimation. However, they fall short on accuracy when they are applied to blurred videos. Some people utilize hybrid camera system to get a low resolution image to suppress the blurring effect so that more accurate optical flow for blurred high resolution image can be further derived, though in most of the practical environments it may not be feasible to deploy hybrid camera systems from cost perspective. In this paper, we propose a novel approach to estimate motion from a blurred video without the use of hybrid camera system, and to reduce motion blur by calculating its spatially varying blur kernels. Essentially, we first separate moving objects into small regions and use the corners of their boundaries as feature points, and then apply Hierarchical Block Matching Algorithm (HBMA) to track them between frames. Motions of non-corner pixels can therefore be estimated by interpolating the motion of these corner points, which further support the calculation of the spatially varying blur kernels for deblurring purpose. Experimental results demonstrate the effectiveness of proposed method.
dc.description.nature	Link_to_subscribed_fulltext
dc.identifier.citation	Proceeding - 5Th International Conference On Computer Sciences And Convergence Information Technology, Iccit 2010, 2010, p. 355-359 [How to Cite?] DOI: http://dx.doi.org/10.1109/ICCIT.2010.5711083
dc.identifier.doi	http://dx.doi.org/10.1109/ICCIT.2010.5711083
dc.identifier.epage	359
dc.identifier.scopus	eid_2-s2.0-79952689989
dc.identifier.spage	355
dc.identifier.uri	http://hdl.handle.net/10722/151997
dc.language	eng
dc.relation.ispartof	Proceeding - 5th International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2010
dc.relation.references	References in Scopus
dc.subject	Deblurring
dc.subject	Motion Estimation
dc.subject	Spatially Varing Blur Kernels
dc.title	Motion estimation method for blurred videos and application of deblurring with spatially varying blur kernels
dc.type	Conference_Paper

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The University of Hong Kong
Unit 107B

Conference Paper: Motion estimation method for blurred videos and application of deblurring with spatially varying blur kernels

The HKU Scholars Hub has contact details for these author(s).