<title>Perceptual quality measure using a spatiotemporal model of the human visual system</title>

Abstract

This paper addresses the problem of quality estimation of digitally coded video sequences. The topic is of great interest since many products in digital video are about to be released and it is thus important t o h a v e robust methodologies for testing and performance evaluation of such devices. The inherent problem is that human vision has to be taken into account in order to assess the quality of a sequence with a good correlation with human judgment. It is well known that the commonly used metric, the signal-to-noise ratio is not correlated with human vision.A metric for the assessment of video coding quality is presented. It is based on a multi-channel model of human spatio-temporal vision that has been parameterized for video coding applications by psychophysical experiments. The visual mechanisms of vision are simulated by a spatio-temporal lter bank. The decomposition is then used to account for phenomena as contrast sensitivity and masking. Once the amount of distortions actually perceived is known, quality estimation can be assessed at various levels. The described metric is able to rate the overall quality of the decoded video sequence as well as the rendition of important features of the sequence such a s contours or textures.

Deinterlacing-an overview

“…Furthermore, we experienced diculties in applying recent proposals, e.g. [46], since publications often do not provide all details while software is not (yet) made available. Some authors expressed their doubt whether their measure was applicable to evaluate de{interlacing.…”

Content-Based Adaptation of Streamed Multimedia

“…The advantage of PSNR is that it is very easy to compute using the Mean Square Error (MSE) of pixel values of luminance for frames from the degraded and reference clips. However, PSNR does not match well to the characteristics of the human vision system (HVS) [15]. However, the main problem with using PSNR values as a quality assessment method is that even though two images may be different, the visibility of this difference is not considered.…”

IPTV quality assessment system

“…The Moving Picture Quality Metric (MPQM) is an objective quality metric for moving pictures using vision modeling approach [13], incorporating two human vision characteristics: contrast sensitivity and masking. Color MPQM is an extension of the MPQM metric which also considers the effect of chrominance on the quality.…”