Objective Human Visual System Based Video Quality Assessment Metric for Low Bit-Rate Video Communication Systems

Quality assessment is crucial to developments of video communication systems. While subjective test yields most accurate results, its expensive cost and human biasness make it an unsatisfactory figure of merit. The peak-signal to noise ratio (PSNR), the most acceptable objective video quality assessment metric, is based on error sensitivity; its failure to capture perceptual errors is well documented. Other perceptual quality metrics fail to detect the localized errors that are common in sequences produced by low bit-rate video communication systems. In this work, a novel perceptual quality assessment metric, the structural similarity (SSIM) metric, is modified to better detect spatial artifacts often seen in video communication systems