Blind Sharpness Prediction for Ultrahigh-Definition Video Based on Human Visual Resolution

Abstract

We explore a no-reference sharpness assessment model for predicting the perceptual sharpness of ultrahigh-definition (UHD) videos through analysis of visual resolution variation in terms of viewing geometry and scene characteristics. The quality and sharpness of UHD videos are influenced by viewer perception of the spatial resolution afforded by the UHD display, which depends on viewing geometry parameters including display resolution, display size, and viewing distance. In addition, viewers may perceive different degrees of quality and sharpness according to the statistical behavior of the visual signals, such as the motion, texture, and edge, which vary over both spatial and temporal domains. The model also accounts for the resolution variation associated with fixation and foveal regions, which is another important factor affecting the sharpness prediction of UHD video over the spatial domain and which is caused by the nonuniform distribution of the photoreceptors. We calculate the transition of the visually salient statistical characteristics resulting from changing the display’s screen size and resolution. Moreover, we calculated the temporal variation in sharpness over consecutive frames in order to evaluate the temporal sharpness perception of UHD video. We verify that the proposed model outperforms other sharpness models in both spatial and temporal sharpness assessments.