Signal Processing: Image Communication, Vol. 19, Feb. 2004, pp. 101-107
Michael H. Brill; Jeffrey Lubin; Pierre Costa; Stephen Wolf; John Pearson
Abstract: Video quality metrics (VQMs) have often been evaluated and compared using simple measures of correlation to subjective mean opinion scores from panels of observers. However, this approach does not fully take into account the variability implicit in the observers. We present techniques for determining the statistical resolving power of a VQM. defined as the minimum change in the value of the metric for which subjective test scores show a significant change. Resolving power is taken as a measure of accuracy. These techniques have been applied to the video quality experts group (VQEG) data set and incorporated into the recent Alliance for Telecommunications Industry Solutions (A TIS) Committee TIA I series of technical reports (TRs), which provide a comprehensive framework for characterizing and validating full-reference VQM. These approved TRs, while not standards, will enable the US telecommunications industry to incorporate VQMs into contracts and tariffs for compressed video distribution. New methods for assessing VQM accuracy and cross-calibrating VQMs are an integral part of the framework. These methods have been applied to two VQMs at this point: peak-signal-to-noise ratio and the version of Sarnoff's just noticeable difference metric (JNDmetrix 11 ) tested by VQEG (Rapporteur Ql l/12 (VQEG): Final report from the VQEG on the validation of objective models of video quality assessment. June 2000). The framework is readily extensible to additional VQMs.
Keywords: standards; telecommunication; video quality; Video Quality Experts Group (VQEG); Quality metrics
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Margaret H. Pinson
Institute for Telecommunication Sciences
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