The National Telecommunications and Information Administration (NTIA) General Model for estimating video quality and its associated calibration techniques were independently evaluated by the Video Quality Experts Group (VQEG) in their Phase II Full Reference Television (FR-TV) test. The NTIA General Model was the only video quality estimator that was in the top performing group for both the 525-line and 625-line video tests. As a result, the American National Standards Institute (ANSI) adopted the NTIA General Model and its associated calibration techniques as a North American Standard in 2003. The International Telecommunication Union (ITU) has also included the NTIA General Model as a normative method in two Draft Recommendations. This paper presents a description of the NTIA General Model and its associated calibration techniques. The independent test results from the VQEG FR-TV Phase II tests are summarized, as well as results from eleven other subjective data sets that were used to develop the method.

The Institute for Telecommunication Sciences (ITS) has developed an objective video quality assessment system that emulates human perception. The perception-based system was developed and tested for a broad range of scenes and video technologies. The 36 test scenes contained widely varying amounts of spatial and temporal information. The 27 impairments included digital video compression systems operating at line rates from 56 kbits/sec to 45 Mbits/sec with controlled error rates, NTSC encode/decode cycles, VHS and S-VHS record/play cycles, and VHF transmission. Subjective viewer ratings of the video quality were gathered in the ITS subjective viewing laboratory that conforms to CCIR Recommendation 500-3. Objective measures of video quality were extracted from the digitally sampled video. These objective measurements are designed to quantify the spatial and temporal distortions perceived by the viewer. This paper presents the following: a detailed description of several of the best ITS objective measurements, a perception-based model that predicts subjective ratings from these objective measurements, and a demonstration of the correlation between the model's predictions and viewer panel ratings.

Many organizations have focused on developing digital video quality metrics which produce results that accurately emulate subjective responses. However, to be widely applicable a metric must also work over a wide range of quality, and be useful for in-service quality monitoring. The Institute for Telecommunication Sciences (ITS) has developed spatial-temporal distortion metrics that meet all of these requirements. These objective metrics are described in detail and have a number of interesting properties, including utilization of (1) spatial activity filters which emphasize long edges on the order of 10 arc min while simultaneously performing large amounts of noise suppression, (2) the angular direction of the spatial gradient, (3) spatial-temporal compression factors of at least 384:1 (spatial compression of at least 64:1 and temporal compression of at least 6:1, and 4) simple perceptibility thresholds and spatial-temporal masking functions. Results are presented that compare the objective metric values with mean opinion scores from a wide range of subjective data bases spanning many different scenes, systems, bit-rates, and applications.

Traditionally, audio quality and video quality are evaluated separately in subjective tests. Best practices within the quality assessment community were developed before many modern mobile audiovisual devices and services came into use, such as internet video, smart phones, tablets and connected televisions. These devices and services raise unique questions that require jointly evaluating both the audio and the video within a subjective test. However, audiovisual subjective testing is a relatively under-explored field. In this paper, we address the question of determining the most suitable way to conduct audiovisual subjective testing on a wide range of audiovisual quality. Six laboratories from four countries conducted a systematic study of audiovisual subjective testing. The stimuli and scale were held constant across experiments and labs; only the environment of the subjective test was varied. Some subjective tests were conducted in controlled environments and some in public environments (a cafeteria, patio or hallway). The audiovisual stimuli spanned a wide range of quality. Results show that these audiovisual subjective tests were highly repeatable from one laboratory and environment to the next. The number of subjects was the most important factor. Based on this experiment, 24 or more subjects are recommended for Absolute Category Rating (ACR) tests. In public environments, 35 subjects were required to obtain the same Student's t-test sensitivity. The second most important variable was individual differences between subjects. Other environmental factors had minimal impact, such as language, country, lighting, background noise, wall color, and monitor calibration. Analyses indicate that Mean Opinion Scores (MOS) are relative rather than absolute. Our analyses show that the results of experiments done in pristine, laboratory environments are highly representative of those devices in actual use, in a typical user environment.

International recommendations for subjective video quality assessment (e.g., ITU-R BT.500-11) include specifications for how to perform many different types of subjective tests. Some of these test methods are double stimulus where viewers rate the quality or change in quality between two video streams (reference and impaired). Others are single stimulus where viewers rate the quality of just one video stream (the impaired). Two examples of the former are the double stimulus continuous quality scale (DSCQS) and double stimulus comparison scale (DSCS). An example of the latter is single stimulus continuous quality evaluation (SSCQE). Each subjective test methodology has claimed advantages. For instance, the DSCQS method is claimed to be less sensitive to context (i.e., subjective ratings are less influenced by the severity and ordering of the impairments within the test session). The SSCQE method is claimed to yield more representative quality estimates for quality monitoring applications. This paper considers data from six different subjective video quality experiments, originally performed with SSCQE, DSCQS and DSCS methodologies. A subset of video clips from each of these six experiments were combined and rated in a secondary SSCQE subjective video quality test. We give a method for post-processing the secondary SSCQE data to produce quality scores that are highly correlated to the original DSCQS and DSCS data. We also provide evidence that human memory effects for time-varying quality estimation seem to be limited to about 15 seconds.

How much bandwidth is required for good quality video for a given screen resolution? Data acquired during two Video Quality Experts Group (VQEG) projects allow at least a partial answer to this question. This international subjective testing produced large amounts of mean opinion score (MOS) data for the screen resolutions QIF, CIF, VGA, and HD; for H.264 and similar modern codecs; and for many bit rates. Those data are assembled in the present report. For each screen resolution, MOS is plotted as a function of bit rate. A plot of all four data sets together shows the bit rate that would be required to achieve a given level of video quality for a given screen resolution. Relations among the four data sets are regular, suggesting that interpolation across screen resolutions might be reasonable. Based on these data, it would be reasonable to choose a bit rate, given a screen resolution; it would not be reasonable to choose a screen resolution given a bit rate.