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 ...
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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 predictionmodel 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 modelbased on fuzzylogicinferencesystem 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 hybridpredictionmodel. This study will help in the development of a reference-free video qualitypredictionmodel and QoS control methods for 4kUHD video streaming.
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