Optimizing Apparent Display Resolution Enhancement for Arbitrary Videos

Abstract

Display resolution is frequently exceeded by available image resolution. Recently, apparent display resolution enhancement (ADRE) techniques show how characteristics of the human visual system can be exploited to provide super-resolution on high refresh rate displays. In this paper, we address the problem of generalizing the ADRE technique to conventional videos of arbitrary content. We propose an optimization-based approach to continuously translate the video frames in such a way that the added motion enables apparent resolution enhancement for the salient image region. The optimization considers the optimal velocity, smoothness, and similarity to compute an appropriate trajectory. In addition, we provide an intuitive user interface that allows to guide the algorithm interactively and preserves important compositions within the video. We present a user study evaluating apparent rendering quality and show versatility of our method on a variety of general test scenes.

A Total Variation Approach for Customizing Imagery to Improve Visual Acuity

“…Within perception [Cornsweet 1970], phenomena such as edge enhancement, opponent-color theory, psychophysical reading aspects (e.g., [Legge et al 1985]), and numerous so-called visual illusions are exploited (e.g., [Wandell 1995;Pizlo et al 2007;Pizlo 2010]). Some approaches combine perceptually-based and ophthalmologically-based techniques for improving image viewing (e.g., [Peli and Woods 2009]) and for improving resolution in videos and animations (e.g., [Didyk et al 2010;Berthouzoz and Fattal 2012a;Berthouzoz and Fattal 2012b;Templin et al 2013;Stengel et al 2013]). For instance, the Cornsweet illusion has been exploited to provide enhanced local contrast [Ritschel et al 2008] and to provide a perceptually-based metric for achieving compelling and efficient stereo disparity [Didyk et al 2011].…”

Temporal Video Filtering and Exposure Control for Perceptual Motion Blur

“…We then assume p(x, t) is defined by the optical flow F i→i+1 (x) [32], [36] for any two frames i and i+1 in I UHFR , which proved successful in related work as well [34], [37]. Nonetheless, it is not a robust solution to simply select the path p(x) of the most salient x to define the global p. Instead, we first mark a set of pixels describing the OOI.…”