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Objective Perceptual Video Quality Prediction Using Spatial and Temporal Information Differences
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2019 (English)In: Proceedings - 2019 19th International Symposium on Communications and Information Technologies, ISCIT 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 436-441Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, objective perceptual video quality models are proposed that use spatial and temporal perceptual information differences for predicting video quality as perceived by human observers. Spatial perceptual information characterizes the complexity and temporal perceptual information quantifies the motion contained in a video. As such, differences in the spatial and temporal perceptual information of a reference video (original) and test video (processed) may be used to predict quality of videos that have undergone encoding, transmission, or other processing. In particular, several video quality prediction functions are derived using curve fitting along with training and validation on data from a publicly available annotated database. The obtained functions provide predicted mean opinion scores as a measure of perceptual quality subject to spatial and temporal perceptual information differences. The analysis of the video quality prediction performance of the proposed models shows that differences in spatial and temporal perceptual information can be used for objective video quality prediction. © 2019 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2019. p. 436-441
Keywords [en]
mean opinion score, objective video quality, quality prediction performance, Spatial perceptual information, temporal perceptual information, video quality prediction, Curve fitting, Forecasting, Mean opinion scores, Perceptual information, Quality prediction, Video quality, Information use
National Category
Telecommunications Computer Sciences
Identifiers
URN: urn:nbn:se:bth-19048DOI: 10.1109/ISCIT.2019.8905186Scopus ID: 2-s2.0-85076234417ISBN: 9781728150093 (print)OAI: oai:DiVA.org:bth-19048DiVA, id: diva2:1381695
Conference
19th International Symposium on Communications and Information Technologies, ISCIT, Ho Chi Minh City, 25 September 2019 through 27 September 2019
Available from: 2019-12-27 Created: 2019-12-27 Last updated: 2019-12-27Bibliographically approved

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Zepernick, Hans-JuergenChu, Thi My ChinhSundstedt, Veronica

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Elwardy, MajedZepernick, Hans-JuergenChu, Thi My ChinhSundstedt, Veronica
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