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dc.contributor.authorSlanina, M.
dc.contributor.authorRicny, V.
dc.date.accessioned2016-03-18T10:36:57Z
dc.date.available2016-03-18T10:36:57Z
dc.date.issued2008-09cs
dc.identifier.citationRadioengineering. 2008, vol. 17, č. 3, s. 103-108. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/57222
dc.description.abstractThe paper presents a video quality metric designed for the H.264/AVC codec. The metric operates directly on the encoded H.264/AVC bit stream, parses the encoding parameters and processes them using an artificial neural network. The network is designed to estimate peak signal-to-noise ratios of the video sequence frames, thus enabling computation of full reference objective quality metric values without having the undistorted video material prior to encoding for comparison. We present the metric framework and test its performance for LDTV (low definition television) as well as HDTV (high definition television) video material.en
dc.formattextcs
dc.format.extent103-108cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2008/08_03_103_108.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectH.264/AVCen
dc.subjectvideo qualityen
dc.subjectobjective quality metricen
dc.subjectHDTVen
dc.subjectartificial neural networken
dc.titleEstimating PSNR in High Definition H.264/AVC Video Sequences Using Artificial Neural Networksen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue3cs
dc.coverage.volume17cs
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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