Visual Preference Prediction for Enhanced Images on Ultra-High-Definition Display

Sewoong Ahn, Woojae Kim, Jinwoo Kim, Jaekyung Kim, Sanghoon Lee

Abstract: Due to the evolution of ultra-high-definition (UHD) technologies, viewers can enjoy more realistic contents. Furthermore, in order to maximize visual attraction, post-processing is conducted in commercial devices. In this paper, we propose a new terminology called visual preference to quantify viewer's preferences for sharpness- and contrast- enhanced UHD images in a particular viewing geometry. Visual preferences depend on the spatial characteristics and are affected by the viewing geometry of display like resolution, display size, and viewing distance. Therefore, we propose a method called visual preference assessment model that accounts for content enhancement features and diverse viewing geometry. By rigorous experiments, our proposed model outperforms other state-of-the-art models.