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Hybrid video quality prediction: Re-viewing video quality measurement for widening application scope
LUNAM Université, Université de Nantes, IRCCyN UMR CNRS 6597, Rue Christian Pauc, 44306 Nantes, France.
TECNALIA, ICT - European Software Institute, Parque Tecnológico de Bizkaia Edificio 202 E-48170 Zamudio, Spain.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. Dept. of Netlab, Acreo Swedish ICT AB, Sweden, . (Realistic3D)ORCID iD: 0000-0001-5060-9402
AGH University of Science and Technology, al. Mickiewicza 30, PL-30059 Kraków, Poland.
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2015 (English)In: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, Vol. 74, no 2, p. 323-343Article in journal (Refereed) Published
Abstract [en]

A 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.

Place, publisher, year, edition, pages
2015. Vol. 74, no 2, p. 323-343
Keywords [en]
Video quality assessment, Human Visual System, Hybrid model development, Perceptual indicators, Quality of Experience
National Category
Media and Communication Technology
Identifiers
URN: urn:nbn:se:miun:diva-19849DOI: 10.1007/s11042-014-1978-2ISI: 000348445300002Scopus ID: 2-s2.0-84921496164Local ID: STCOAI: oai:DiVA.org:miun-19849DiVA, id: diva2:647239
Available from: 2013-09-10 Created: 2013-09-10 Last updated: 2018-01-11Bibliographically approved

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Brunnström, Kjell

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