Share Email Print

Journal of Electronic Imaging

Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models
Author(s): Muhammad Shahid; Katerina Pandremmenou; Lisimachos P. Kondi; Andreas Rossholm; Benny Lövström
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 20 September 2016
PDF: 26 pages
J. Electron. Imag. 25(5) 053012 doi: 10.1117/1.JEI.25.5.053012
Published in: Journal of Electronic Imaging Volume 25, Issue 5
Show Author Affiliations
Muhammad Shahid, Blekinge Institute of Technology (Sweden)
Prince Sultan Univ. (Saudi Arabia)
Katerina Pandremmenou, Univ. of Ioannina (Greece)
Lisimachos P. Kondi, Univ. of Ioannina (Greece)
Andreas Rossholm, Blekinge Institute of Technology (Sweden)
Benny Lövström, Blekinge Institute of Technology (Sweden)

© SPIE. Terms of Use
Back to Top