Video accounts for more than 75 percent of internet traffic. High resolution videos are streamed and degraded in the process. As viewers demand high Quality of Experience (QoE), video providers and end users will benefit from a cost-effective objective reference-only quality metric that accurately simulates the subjective QoE. The reference-only Predicted Video Quality (PVQ) metric presented here meets these needs. The reference-only PVQ metric was developed by dividing training videos into four groups based on their Sum of Absolute Differences (SAD), Edginess, Brightness, and Blurriness. Each video was then subjected to degradations based on desired frame rates, bitrates, and packet error rates. The resultant Peak Signal-to-Noise Ratio (PSNR) were used to generate best fit coefficients for each group. The reference-only PVQ metric was tested and shown have low error mean and standard deviation.
