Comparison of Video Quality Metrics on Multimedia Videos

Comparing apples and oranges: assessment of the relative video quality in the presence of different types of distortions

“…We have shown that DSAQFA can substantially facilitate the subjective assessment process in these kinds of scenarios. In the related work, Loke et al [23] have used impairment scaling with DSIS method variant II and Seshadrinathan et al [24] have used continuous MOS scaling in a single stimulus test arrangement. These methods are feasible for such studies, but they do not solve the uncertainties related to quality ratings, as discussed in Section 2.2.…”

“…Kotevski and Pece [22] have used video sequences with artifacts such as hue, saturation, and Gaussian noise, which are not relevant for a typical real-life multimedia communications scenario. Loke et al [23] have compared objective metrics subjected to H.264 and MPEG-4 video compression at different bitrates. Therefore, the results are useful for evaluating how well the studied objective metrics assess the impact of source distortion, but the results cannot be generalized for channel distortion.…”

“…Several related studies have been conducted to compare the performance of different objective video quality models [22][23][24]. Typically, the metrics are evaluated by computing the correlation between the subjective MOS and the objective quality index.…”

NR-Bitstream video quality metrics for SSIM using encoding decisions in AVC and HEVC coded videos

“…Another popular FR metric is Video Quality Metric (VQM) [5], which is developed by the National Telecommunication and Information Administration. VQM is shown to be well correlated with human perception [6]. RR metrics use partial information about the original video and are sent reliably to the video quality monitoring device to estimate the video quality.…”

Perceptual video quality optimization in AWGN channel using low complexity channel code rate allocation

“…In this paper, we reduce the complexity of our algorithm presented in [7] by preprocessing the packet information using k-means clustering. We evaluate the decoded lossy video using Video Quality Metric (VQM) [9, 10], a full reference (FR) metric developed by the National Telecommunication and Information Administration, shown to be well correlated with human perception compared to other FR video quality metrics [11]. The proposed algorithm has much lower complexity, and performs slightly better than the prior algorithm.…”