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.
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. In addition to displaying the video sequences in different ways, subjective tests also have different rating scales, different words associated with these scales, and many other test variables that change from one laboratory to another (e.g., viewer expertise and criticality, cultural differences, physical test environments). Thus, it is very difficult to directly compare or combine results from two or more subjective experiments. The ability to compare and combine results from multiple subjective experiments would greatly benefit developers and users of video technology since standardized subjective data bases could be expanded upon to include new source material and past measurement results could be related to newer measurement results. This paper presents a subjective method and an objective method for combining multiple subjective data sets. The subjective method utilizes a large meta-test with selected video clips from each subjective data set. The objective method utilizes the functional relationships between objective video quality metrics (extracted from the video sequences) and corresponding subjective mean opinion scores (MOSs). The objective mapping algorithm, called the iterated nested least-squares algorithm (INLSA), relates two or more independent data sets that are themselves correlated with some common intermediate variables (i.e, the objective video quality metrics). We demonstrate that the objective method can be used as an effective substitute for the expensive and time consuming subjective meta-test.
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.
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.
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