Evaluation of Wirelessly Transmitted Video Quality Using a Modular Fuzzy Logic System

SALAMA, Abdussalam and SAATCHI, Reza (2019). Evaluation of Wirelessly Transmitted Video Quality Using a Modular Fuzzy Logic System. Technologies, 7 (3), p. 67.

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Abstract

Video transmission over wireless computer networks is increasingly popular as new applications emerge and wireless networks become more widespread and reliable. An ability to quantify the quality of a video transmitted using a wireless computer network is important for determining network performance and its improvement. The process requires analysing the images making up the video from the point of view of noise and associated distortion as well as traffic parameters represented by packet delay, jitter and loss. In this study a modular fuzzy logic based system was developed to quantify the quality of video transmission over a wireless computer network. Peak signal to noise ratio, structural similarity index and image difference were used to represent the user's quality of experience (QoE) while packet delay, jitter and percentage packet loss ratio were used to represent traffic related quality of service (QoS). An overall measure of the video quality was obtained by combining QoE and QoS values. Systematic sampling was used to reduce the number of images processed and a novel scheme was devised whereby the images were partitioned to more sensitively localize distortions. To further validate the developed system, a subjective test involving 25 participants graded the quality of the received video. The image partitioning significantly improved the video quality evaluation. The subjective test results correlated with the developed fuzzy logic approach. The video quality assessment developed in this study was compared against a method that uses spatial efficient entropic differencing and consistent results were observed. The study indicated that the developed fuzzy logic approaches could accurately determine the quality of a wirelessly transmitted video.

Item Type:	Article
Identification Number:	https://doi.org/10.3390/technologies7030067
Page Range:	p. 67
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	16 Sep 2019 10:05
Last Modified:	18 Mar 2021 03:34
URI:	https://shura.shu.ac.uk/id/eprint/25141

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