Quality control
Feb 1, 2010 12:00 PM, By Richard Duvall
Understanding PQR, DMOS and PSNR measurements
This parameter is a generalized mean of the perceptual contrast differences between the best case and worst case training video sequences associated with the DMOS measurement. This generalized mean, called the Minkowski metric or k-Minkowksi metric, was calculated by performing a perceptual-based picture quality measurement, either PQR or DMOS, using the best case video sequence as the reference video and the worst case video sequence as the test video in the measurement.
Instruments offer preconfigured DMOS measurements that contain different values for the worst case training sequence response parameter, determined by using video sequences appropriate for the measurement. These serve as templates for creating custom measurements that more precisely address a specific application's characteristics and requirements for picture quality evaluation.
Interpreting DMOS measurements
Figure 4 shows a typical DMOS measurement. In the preconfigured DMOS measurements, values in the 0-20 range indicate test video that viewers would rate as excellent to good relative to the reference video. Results in the 21-40 range correspond to viewers' subjective ratings of fair to poor quality video. DMOS values above 40 indicate the test video has poor to bad quality relative to the reference video.
DMOS measurements predict the DMOS values viewers would give the reference and test videos used in the measurement if they evaluated these videos in a subjective evaluation conducted according to procedures defined in ITU-R BT.500.
The same test videos can receive different DMOS values from different viewer audiences. It depends on the video sequences used to train the viewers. Similarly, DMOS measurements configured with the same display technology and viewing conditions can produce different results if they are also configured with different worst case training sequence responses.
In this sense, the DMOS measurement is a relative scale. The DMOS value depends on the worst case training sequence response used to configure the measurement, just as the results of the associated ITU-R BT.500 subjective evaluation depend on the video sequences used to train the viewing audience. When comparing DMOS measurement results, evaluators need to verify that the measurements use the same display technologies, viewing conditions and worst case training sequence response parameters.
The DMOS measurement is an excellent choice for picture quality evaluation teams needing to understand and quantify how differences between a reference and test video degrade subjective video quality. The PQR measurement complements the DMOS measurement by helping these teams determine if viewers can notice this difference, especially near the visibility threshold.
PSNR measurements
To calculate a PSNR value, an instrument computes the root mean squared (RMS) difference between the reference and test video and divides this into the peak value. It computes the PSNR value for every frame in the test video and for the entire video sequence. In PSNR measurements, as the difference between the reference and test video increases, the PSNR measurement result decreases.
Combining PSNR measurements with the perceptual-based measurements offers unique insight into the impact of differences between the reference and test videos. Figure 5 shows a comparison of a PSNR measurement in Mean Absolute LSBs units (solid blue line) and a DMOS measurement (dotted magenta line). The PSNR measurement shows when differences occur between the two video sequences. The DMOS measurement shows the perceptual impact of these differences.
In these comparison graphs, evaluation teams can see how differences do, or do not, impact perceived quality. They can see how adaptation in the visual system affects viewers' perception. For example, a large transition in average luminance during a scene change can mask differences. Comparing the difference map created in the PSNR measurement and the perceptual contrast difference map created in a PQR or DMOS measurement can reveal problem regions within the video field or frame. These comparisons can help engineers more easily map visual problems to hardware or software faults.
Conclusion
Engineering and quality assurance teams need to perform frequent, repeated and accurate picture quality assessments to diagnose picture quality problems; optimize product designs; qualify video equipment; optimize video system performance; and produce, distribute and repurpose high-quality video content. They cannot afford the time and expense associated with recruiting viewers, configuring tests and conducting subjective viewer assessments. They need objective picture quality measurements that can make these assessments more quickly than subjective evaluation and at a lower cost. However, these objective measurements should match subjective evaluations as closely as possible.
Full-reference objective picture quality measurements address these requirements. The perceptual-based DMOS and PQR measurements offer results well matched to subjective evaluations. Over a wide range of impairments and conditions, DMOS measurements can help evaluation teams determine how differences between reference and test videos can affect subjective quality ratings. PQR measurements can help these teams determine to what extent viewers will notice these differences, especially for applications that place a premium on high-quality video.
Richard Duvall is the Americas video marketing manager for Tektronix.
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