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dc.contributor.authorBarkowsky, Marcus
dc.contributor.authorSedano, Inigo
dc.contributor.authorBrunnstrom, Kjell
dc.contributor.authorLeszczuk, Mikolaj
dc.contributor.authorStaelens, Nicolas
dc.date.accessioned2016-06-22T10:36:59Z
dc.date.available2016-06-22T10:36:59Z
dc.date.issued2015-01
dc.identifier.citationMultimedia Tools and Applications, January 2015, Volume 74, Issue 2, pp 323–343en
dc.identifier.issn1380-7501en
dc.identifier.urihttp://hdl.handle.net/11556/260
dc.description.abstractA tremendous number of objective video quality measurement algorithms have been developed during the last two decades. Most of them either measure a very limited aspect of the perceived video quality or they measure broad ranges of quality with limited prediction accuracy. This paper lists several perceptual artifacts that may be computationally measured in an isolated algorithm and some of the modeling approaches that have been proposed to predict the resulting quality from those algorithms. These algorithms usually have a very limited application scope but have been verified carefully. The paper continues with a review of some standardized and well-known video quality measurement algorithms that are meant for a wide range of applications, thus have a larger scope. Their individual artifacts prediction accuracy is usually lower but some of them were validated to perform sufficiently well for standardization. Several difficulties and shortcomings in developing a general purpose model with high prediction performance are identified such as a common objective quality scale or the behavior of individual indicators when confronted with stimuli that are out of their prediction scope. The paper concludes with a systematic framework approach to tackle the development of a hybrid video quality measurement in a joint research collaboration.en
dc.description.sponsorshipPolish National Centre for Research and Development (NCRD) SP/I/1/77065/10, Swedish Governmental Agency for Innovation Systems (Vinnova)en
dc.language.isoengen
dc.publisherSPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDSen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleHybrid video quality prediction: reviewing video quality measurement for widening application scopeen
dc.typearticleen
dc.identifier.doi10.1007/s11042-014-1978-2en
dc.isiYesen
dc.rights.accessRightsopenAccessen
dc.subject.keywordsVideo quality assessmenten
dc.subject.keywordsHuman visual systemen
dc.subject.keywordsHybrid model developmenten
dc.subject.keywordsPerceptual indicatorsen
dc.subject.keywordsQuality of Experienceen


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    Attribution 4.0 InternationalExcept where otherwise noted, this item's license is described as Attribution 4.0 International