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Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models

[+] Author Affiliations
Muhammad Shahid

Blekinge Institute of Technology, Karlskrona 37179, Sweden

Prince Sultan University, Rafha Street, Riyadh 12435, Saudi Arabia

Katerina Pandremmenou, Lisimachos P. Kondi

University of Ioannina, Department of Computer Science & Engineering, Ioannina GR-45110, Greece

Andreas Rossholm, Benny Lövström

Blekinge Institute of Technology, Karlskrona 37179, Sweden

J. Electron. Imaging. 25(5), 053012 (Sep 20, 2016). doi:10.1117/1.JEI.25.5.053012
History: Received October 26, 2015; Accepted August 23, 2016
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Abstract.  Reduced-reference (RR) and no-reference (NR) models for video quality estimation, using features that account for the impact of coding artifacts, spatio-temporal complexity, and packet losses, are proposed. The purpose of this study is to analyze a number of potentially quality-relevant features in order to select the most suitable set of features for building the desired models. The proposed sets of features have not been used in the literature and some of the features are used for the first time in this study. The features are employed by the least absolute shrinkage and selection operator (LASSO), which selects only the most influential of them toward perceptual quality. For comparison, we apply feature selection in the complete feature sets and ridge regression on the reduced sets. The models are validated using a database of H.264/AVC encoded videos that were subjectively assessed for quality in an ITU-T compliant laboratory. We infer that just two features selected by RR LASSO and two bitstream-based features selected by NR LASSO are able to estimate perceptual quality with high accuracy, higher than that of ridge, which uses more features. The comparisons with competing works and two full-reference metrics also verify the superiority of our models.

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Topics

Video

Citation

Muhammad Shahid ; Katerina Pandremmenou ; Lisimachos P. Kondi ; Andreas Rossholm and Benny Lövström
"Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models", J. Electron. Imaging. 25(5), 053012 (Sep 20, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.5.053012


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