An error-based video quality assessment method
with temporal information
David Boon Liang Bong
Received: 26 July 2017 /Revised: 27 March 2018 /Accepted: 8 May 2018
Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract Videos are amongst the most popular online media for Internet users nowadays. Thus,
it is of utmost importance that the videos transmitted through the internet or other transmission
media to have a minimal data loss and acceptable visual quality. Video quality assessment (VQA)
is a useful tool to determine the quality of a video without human intervention. A new VQA
method, termed as Error and Temporal Structural Similarity (EaTSS), is proposed in this paper.
EaTSS is based on a combination of error signals, weighted Structural Similarity Index (SSIM)
and difference of temporal information. The error signals are used to weight the computed SSIM
map and subsequently to compute the quality score. This is a better alternative to the usual SSIM
index, in which the quality score is computed as the average of the SSIM map. For the temporal
information, the second-order time-differential information are used for quality score computa-
tion. From the experiments, EaTSS is found to have competitive performance and faster
computational speed compared to other existing VQA algorithms.
Keywords Video quality
Many multimedia applications deal with visual assets nowadays. This is more evident in
mobile devices such as smartphones, tablets, smart watches, and smart glasses. These devices
use microprocessors or microcontrollers with high processing ability. This processing ability
enables them to process data on their own without relying on external processing devices.
According to the research done by Ooyala , mobile video views increased from 6.3% of
the overall mobile traffic data in 2012 to 45.1% in Q3 2015. This shows the importance of
videos in multimedia equipment. Assessment of the video qualities of these products is crucial
as a quality feedback tool for device manufacturers and content service providers.
Multimed Tools Appl
* David Boon Liang Bong
Faculty of Engineering, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia