Motion blur detection based on lowest directional high-frequency energy

Chen, X; Yang, J; Wu, Q; Zhao, J

Motion blur detection based on lowest directional high-frequency energy

Chen, X Yang, J Wu, Q

Zhao, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Conference on Image Processing, ICIP, 2010, pp. 2533 - 2536
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Chen, X	en_US
dc.contributor.author	Yang, J	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	Zhao, J	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Proceedings - International Conference on Image Processing, ICIP, 2010, pp. 2533 - 2536	en_US
dc.identifier.isbn	9781424479948	en_US
dc.identifier.issn	1522-4880	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16120
dc.description.abstract	Motion blur detection and the relevant blurring parameter estimation are important for many computer vision tasks. The contribution of this paper is in two folds. First, we propose a closed-form solution for motion direction estimation on blurred image. Secondly, a novel method is proposed for motion blurred region detection. The proposed direction estimation is based on measurement of lowest directional high-frequency energy. Compared with traditional methods, it will improve accuracy with less computational cost. Moreover, the proposed motion blurred region detection can efficiently estimate blurred regions without Point Spread Function estimation. Encouraging results are shown by experiments. © 2010 IEEE.	en_US
dc.relation.ispartof	Proceedings - International Conference on Image Processing, ICIP	en_US
dc.relation.isbasedon	10.1109/ICIP.2010.5652935	en_US
dc.title	Motion blur detection based on lowest directional high-frequency energy	en_US
dc.type	Conference Proceeding
utslib.for	080106 Image Processing	en_US
dc.location.activity	Hongkong	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Motion blur detection and the relevant blurring parameter estimation are important for many computer vision tasks. The contribution of this paper is in two folds. First, we propose a closed-form solution for motion direction estimation on blurred image. Secondly, a novel method is proposed for motion blurred region detection. The proposed direction estimation is based on measurement of lowest directional high-frequency energy. Compared with traditional methods, it will improve accuracy with less computational cost. Moreover, the proposed motion blurred region detection can efficiently estimate blurred regions without Point Spread Function estimation. Encouraging results are shown by experiments. © 2010 IEEE.

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http://hdl.handle.net/10453/16120