Video quality assessment (VQA) exploits important properties of the sophisticated human visual system (HVS). In this paper, we study a series of fundamental HVS characteristics for subjective video quality assessment, and incorporate them into a systematic framework to simulate subjective evaluation on impaired videos. Based on this framework, we develop a novel full-reference metric, namely, perceptual quality index (PQI). Specifically, the proposed PQI metric comprises four major modules: 1) visual performance equation for the foveal and extra-foveal vision based on the cortical magnification theory; 2) perceptible noise detection using a spatial-temporal just noticeable difference model, and its quantification in both spatial and temporal channels, considering the varying error sensitivity due to the contrast and motion masking effects; 3) instantaneous error summation with inhibition of weak local distortions, and quality degradation accumulation over time that models the visual persistence and recency effect; and 4) fusion of the spatial and temporal noise intensities into a perceptual quality index. Compared with some state-of-the-art VQA models, the PQI metric, which exploits multiple visual properties, measures video quality more accurately and reliably on two VQA databases.
['Yin Zhao', 'Lu Yu', 'Zhenzhong Chen', 'Ce Zhu']
Video Quality Assessment Based on Measuring Perceptual Noise From Spatial and Temporal Perspectives