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dc.contributor.authorPérez-Pellitero, Eduardo
dc.contributor.authorSalvador, Jordi
dc.contributor.authorRuiz Hidalgo, Javier
dc.contributor.authorRosenhahn, Bodo
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2015-10-26T14:41:28Z
dc.date.issued2015
dc.identifier.citationPérez-Pellitero, E., Salvador, J., Ruiz-Hidalgo, J., Rosenhahn, B. Accelerating super-resolution for 4K upscaling. A: International Conference on Consumer Electronics. "2015 IEEE International Conference on Consumer Electronics (ICCE 2015): Las Vegas, Nevada, USA: 9-12 January 2015". Las Vegas, Nevada: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 317-320.
dc.identifier.isbn9781479975440
dc.identifier.urihttp://hdl.handle.net/2117/78255
dc.description.abstractThis paper presents a fast Super-Resolution (SR) algorithm based on a selective patch processing. Motivated by the observation that some regions of images are smooth and unfocused and can be properly upscaled with fast interpolation methods, we locally estimate the probability of performing a degradation-free upscaling. Our proposed framework explores the usage of supervised machine learning techniques and tackles the problem using binary boosted tree classifiers. The applied upscaler is chosen based on the obtained probabilities: (1) A fast upscaler (e.g. bicubic interpolation) for those regions which are smooth or (2) a linear regression SR algorithm for those which are ill-posed. The proposed strategy accelerates SR by only processing the regions which benefit from it, thus not compromising quality. Furthermore all the algorithms composing the pipeline are naturally parallelizable and further speed-ups could be obtained.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.lcshImage processing
dc.subject.lcshArtificial intelligence
dc.subject.otherImage classification
dc.subject.otherImage resolution
dc.subject.otherInterpolation
dc.subject.otherLearning (artificial intelligence)
dc.subject.otherProbability
dc.subject.otherRegression analysis
dc.subject.otherTrees (mathematics)
dc.titleAccelerating super-resolution for 4K upscaling
dc.typeConference report
dc.subject.lemacImatges -- Processament
dc.subject.lemacIntel·ligència artificial
dc.contributor.groupUniversitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
dc.identifier.doi10.1109/ICCE.2015.7066429
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7066429
dc.rights.accessRestricted access - publisher's policy
drac.iddocument15572551
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorPérez-Pellitero, E.; Salvador, J.; Ruiz-Hidalgo, J.; Rosenhahn, B.
upcommons.citation.contributorInternational Conference on Consumer Electronics
upcommons.citation.pubplaceLas Vegas, Nevada
upcommons.citation.publishedtrue
upcommons.citation.publicationName2015 IEEE International Conference on Consumer Electronics (ICCE 2015): Las Vegas, Nevada, USA: 9-12 January 2015
upcommons.citation.startingPage317
upcommons.citation.endingPage320


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