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Fuzzy logic inference system-based hybrid quality prediction model for wireless 4kUHD H.265-coded video streaming

Alreshoodi, M, Adeyemi-Ejeye, Anthony, Woods, J and Walker, SD (2015) Fuzzy logic inference system-based hybrid quality prediction model for wireless 4kUHD H.265-coded video streaming IET Networks. Special Issue on Creating a Smarter Environment through the Advancement of Communication Systems, Networks and Applications, 4 (6). pp. 296-303.

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Abstract

Networked visual applications such video streaming have grown exponentially in recent years, yet are known to be sensitive to network impairments. However, available measurement techniques that adopt a full reference model are impractical in real-time streaming because they require the original video sequence available at the receivers side. The primary aim of this study is to present a hybrid no-reference prediction model for the perceptual quality of 4kUHD H.265-coded video in the wireless domain. The contributions of this paper are two-fold: first, an investigation of the impact of quality of service (QoS) parameters on 4kUHD H.265-coded video transmission in an experimental environment; second, objective model based on fuzzy logic inference system is developed to predict the visual quality by mapping QoS parameters to the measured quality of experience. The model is evaluated in contrast to random neural networks. The results show that good prediction accuracy was obtained from the proposed hybrid prediction model. This study will help in the development of a reference-free video quality prediction model and QoS control methods for 4kUHD video streaming.

Item Type: Article
Divisions : Faculty of Arts and Social Sciences > School of Arts > Music
Authors :
NameEmailORCID
Alreshoodi, MUNSPECIFIEDUNSPECIFIED
Adeyemi-Ejeye, Anthonya.adeyemi-ejeye@surrey.ac.ukUNSPECIFIED
Woods, JUNSPECIFIEDUNSPECIFIED
Walker, SDUNSPECIFIEDUNSPECIFIED
Date : 2015
Identification Number : 10.1049/iet-net.2015.0018
Copyright Disclaimer : Copyright 2015 The Institution of Engineering and Technology
Depositing User : Melanie Hughes
Date Deposited : 29 Sep 2017 12:26
Last Modified : 29 Sep 2017 12:26
URI: http://epubs.surrey.ac.uk/id/eprint/842435

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