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Conference Paper: Nonlinear image reconstruction in block-based compressive imaging

TitleNonlinear image reconstruction in block-based compressive imaging
Authors
Ke, JLam, EYM
KeywordsCompressive imaging
Feature measurement
Learning frameworks
Projection vectors
Reconstruction problems
Issue Date2012
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000089
Citation
The 2012 IEEE International Symposium on Circuits and Systems (ISCAS), Seoul, Korea, 20-23 May 2012. In IEEE International Symposium on Circuits and Systems Proceedings, 2012, p. 2917-2920 How to Cite?
DOI: http://dx.doi.org/10.1109/ISCAS.2012.6271926
AbstractA block-based compressive imaging (BCI) system with sequential architecture is presented in this paper. Feature measurements are collected using the principal component analysis (PCA) projection vectors. Then, we discuss an object prior learning framework based on the Field-of-Expert (FoE) model, and provide its implementation in the BCI reconstruction problem. Experimental results are used to demonstrate the reconstruction performance of the FoE-based method. © 2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/153066
ISBN
978-1-4673-0219-7
ISSN
0271-4302

 

DC FieldValueLanguage
dc.contributor.authorKe, Jen_US
dc.contributor.authorLam, EYMen_US
dc.date.accessioned2012-07-16T09:55:42Z-
dc.date.available2012-07-16T09:55:42Z-
dc.date.issued2012en_US
dc.identifier.citationThe 2012 IEEE International Symposium on Circuits and Systems (ISCAS), Seoul, Korea, 20-23 May 2012. In IEEE International Symposium on Circuits and Systems Proceedings, 2012, p. 2917-2920en_US
dc.identifier.isbn978-1-4673-0219-7-
dc.identifier.issn0271-4302-
dc.identifier.urihttp://hdl.handle.net/10722/153066-
dc.description.abstractA block-based compressive imaging (BCI) system with sequential architecture is presented in this paper. Feature measurements are collected using the principal component analysis (PCA) projection vectors. Then, we discuss an object prior learning framework based on the Field-of-Expert (FoE) model, and provide its implementation in the BCI reconstruction problem. Experimental results are used to demonstrate the reconstruction performance of the FoE-based method. © 2012 IEEE.-
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.subjectCompressive imaging-
dc.subjectFeature measurement-
dc.subjectLearning frameworks-
dc.subjectProjection vectors-
dc.subjectReconstruction problems-
dc.titleNonlinear image reconstruction in block-based compressive imagingen_US
dc.typeConference_Paperen_US
dc.identifier.emailKe, J: junke@eee.hku.hken_US
dc.identifier.emailLam, EYM: elam@eee.hku.hken_US
dc.identifier.authorityLam, EYM=rp00131en_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ISCAS.2012.6271926-
dc.identifier.scopuseid_2-s2.0-84866624413-
dc.identifier.hkuros200970en_US
dc.identifier.spage2917-
dc.identifier.epage2920-
dc.publisher.placeUnited States-
dc.description.otherThe 2012 IEEE International Symposium on Circuits and Systems (ISCAS), Seoul, Korea, 20-23 May 2012. In IEEE International Symposium on Circuits and Systems Proceedings, 2012, p. 2917-2920-
dc.identifier.issnl0271-4302-

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