Szczegóły publikacji

Opis bibliograficzny

Hybrid video quality prediction: reviewing video quality measurement for widening application scope / Marcus Barkowsky, Iñigo Sedano, Kjell Brunnström, Mikołaj LESZCZUK, Nicolas Staelens // Multimedia Tools and Applications ; ISSN 1380-7501. — 2015 — vol. 74 iss. 2, s. 323–343. — Bibliogr. s. 338–341, Abstr. — Publikacja dostępna online od: 2014-04-24

Autorzy (5)

Słowa kluczowe

hybrid model developmentperceptual indicatorsQuality of Experiencehuman visual systemvideo quality assessment

Dane bibliometryczne

ID BaDAP103584
Data dodania do BaDAP2017-01-24
Tekst źródłowyURL
DOI10.1007/s11042-014-1978-2
Rok publikacji2015
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaMultimedia Tools and Applications

Abstract

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.

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