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Conference Paper: Fast single frame super-resolution using scale-invariant self-similarity

TitleFast single frame super-resolution using scale-invariant self-similarity
Authors
Issue Date2013
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000089
Citation
The 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), Beijing, China, 19-23 May 2013. In IEEE International Symposium on Circuits and Systems Proceedings, 2013, p. 1191-1194 How to Cite?
AbstractExample-based super-resolution (SR) attracts great interest due to its wide range of applications. However, these algorithms usually involve patch search in a large database or the input image, which is computationally intensive. In this paper, we propose a scale-invariant self-similarity (SiSS) based super-resolution method. Instead of searching patches, we select the patch according to the SiSS measurement, so that the computational complexity is significantly reduced. Multi-shaped and multi-sized patches are used to collect sufficient patches for high-resolution (HR) image reconstruction and a hybrid weighting method is used to suppress the artifacts. Experimental results show that the proposed algorithm is 20~1,800 times faster than several state-of-the-art approaches and can achieve comparable quality.
Persistent Identifierhttp://hdl.handle.net/10722/186795
ISBN
ISSN

 

DC FieldValueLanguage
dc.contributor.authorLiang, Len_US
dc.contributor.authorChiu, KHen_US
dc.contributor.authorLam, EYen_US
dc.date.accessioned2013-08-20T12:19:31Z-
dc.date.available2013-08-20T12:19:31Z-
dc.date.issued2013en_US
dc.identifier.citationThe 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), Beijing, China, 19-23 May 2013. In IEEE International Symposium on Circuits and Systems Proceedings, 2013, p. 1191-1194en_US
dc.identifier.isbn978-1-4673-5762-3-
dc.identifier.issn0271-4302-
dc.identifier.urihttp://hdl.handle.net/10722/186795-
dc.description.abstractExample-based super-resolution (SR) attracts great interest due to its wide range of applications. However, these algorithms usually involve patch search in a large database or the input image, which is computationally intensive. In this paper, we propose a scale-invariant self-similarity (SiSS) based super-resolution method. Instead of searching patches, we select the patch according to the SiSS measurement, so that the computational complexity is significantly reduced. Multi-shaped and multi-sized patches are used to collect sufficient patches for high-resolution (HR) image reconstruction and a hybrid weighting method is used to suppress the artifacts. Experimental results show that the proposed algorithm is 20~1,800 times faster than several state-of-the-art approaches and can achieve comparable quality.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000089-
dc.relation.ispartofIEEE International Symposium on Circuits and Systems Proceedingsen_US
dc.titleFast single frame super-resolution using scale-invariant self-similarityen_US
dc.typeConference_Paperen_US
dc.identifier.emailLiang, L: luhongliang@astri.orgen_US
dc.identifier.emailChiu, KH: khchiu@astri.org-
dc.identifier.emailLam, EY: elam@eee.hku.hk-
dc.identifier.authorityLam, EY=rp00131en_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ISCAS.2013.6572065-
dc.identifier.scopuseid_2-s2.0-84883373843-
dc.identifier.hkuros220501en_US
dc.identifier.spage1191-
dc.identifier.epage1194-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 130903-

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