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Multimed Tools Appl (2015) 74:323343
DOI 10.1007/s11042-014-1978-2
Marcus Barkowsky & Iigo Sedano & Kjell Brunnstrm & Mikoaj Leszczuk & Nicolas Staelens
Published online: 24 April 2014# The Author(s) 2014. This article is published with open access at Springerlink.com
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.
M. Barkowsky (*)
LUNAM Universit, Universit de Nantes, IRCCyN UMR CNRS 6597, Rue Christian Pauc, 44306 Nantes, Francee-mail: [email protected]
I. Sedano
TECNALIA, ICT - European Software Institute, Parque Tecnolgico de Bizkaia, Edificio 202, 48170 Zamudio, Spaine-mail: [email protected]
K. Brunnstrm
Department of Netlab, Acreo Swedish ICT AB (and Mid Sweden University), Stockholm, Sweden e-mail: [email protected]
M. Leszczuk (*)
AGH University of Science and Technology, al. Mickiewicza 30, 30059 Krakw, Poland e-mail: [email protected]
N. Staelens
Department of Information Technology, Ghent University - iMinds, Ghent, Belgium e-mail: [email protected]
Hybrid video quality prediction: reviewing video quality measurement for widening application scope
324 Multimed Tools Appl (2015) 74:323343
Keywords Video quality assessment . Human visual system . Hybrid model development . Perceptual indicators . Quality of Experience
1 Introduction
Video quality assessment has been an important topic during the last...