Chapter 41 in The
Handbook of Video Databases: Design and Applications, B. Furht and O. Marqure, ed., CRC Press, pp. 1041-1078,
Sept. 2003
Objective Video Quality
Assessment
Zhou
Wang, Hamid R. Sheikh and Alan C. Bovik
Laboratory for Image and Video Engineering (LIVE),
The
Abstract:
Digital video data, stored in video databases and distributed
through communication networks, is subject to various kinds of distortions
during acquisition, compression, processing, transmission, and reproduction. It
is imperative for a video service system to be able to realize and quantify the
video quality degradations that occur in the system, so that it can maintain,
control and possibly enhance the quality of the video data. An effective image
and video quality metric is crucial for this purpose. The goal of objective
image and video quality assessment research is to design quality metrics that
can predict perceived image and video quality automatically. Such a metric can
be used to monitor image quality for quality control systems. It can be
employed to benchmark image and video processing systems and algorithms.
It can also be embedded into an image and video processing system to optimize
the algorithms and the parameter settings. This chapter mainly focuses
on the basic concepts, ideas and approaches for image and video quality
assessment. We first review the background and various implementations of a
widely adopted error-sensitivity based philosophy for quality assessment and
attempt to point out its limitations. We then introduce a new way to think
about the problem of image and video quality assessment and provide some
preliminary results of a novel structural distortion based quality assessment
method. Next, we introduce the current status of quality assessment research
for the cases that the reference images are not or only partially available. We
also discuss the issues that are related to the validation of image and video
quality metrics, including the recent effort by the video quality experts group
(VQEG) in developing, validating and standardizing video quality metrics for
television and multimedia applications. Finally, we make some concluding
remarks and provide a vision for future directions of image and video quality
assessment.
Index Terms – Image and video
quality assessment, perceptual quality, human visual system (HVS), error
sensitivity, structural distortion, video quality experts group (VQEG)