Perceptually-based compensation of light pollution in display systems

Jeroen van Baar, Steven Poulakos, Wojciech Jarosz, Derek Nowrouzezahrai, Rasmus Tamstorf, Markus Gross
2011 Proceedings of the ACM SIGGRAPH Symposium on Applied Perception in Graphics and Visualization - APGV '11  
Projected Image Observed Image Subtractive Deghosting Our Perceptual Deghosting Subtractive Descattering Our Perceptual Descattering Figure 1 : Using our perceptual framework we can compensate for light pollution due to ghosting in 3D stereo (left) and indirect scattering when projecting onto concave screens (right). Current subtractive solutions fail in areas where the input image is dark (by either retaining some residual ghost or eliminating important surface detail). Our solution
more » ... ly solves for a perceptually optimal compensation that diminishes the appearance of ghosts and reveals more detail in these problem regions. Note: All deghosting results in this paper have been captured with a camera through a polarizing filter; All descattering results are simulations Abstract This paper addresses the problem of unintended light contributions due to physical properties of display systems. An example of such unintended contribution is crosstalk in stereoscopic 3D display systems, often referred to as ghosting. Ghosting results in a reduction of visual quality, and may lead to an uncomfortable viewing experience. The latter is due to conflicting (depth) edge cues, which can hinder the human visual system (HVS) proper fusion of stereo images (stereopsis). We propose an automatic, perceptually-based computational compensation framework, which formulates pollution elimination as a minimization problem. Our method aims to distribute the error introduced by the pollution in a perceptually optimal manner. As a consequence ghost edges are smoothed locally, resulting in a more comfortable stereo viewing experience. We show how to make the computation tractable by exploiting the structure of the resulting problem, and also propose a perceptually-based pollution prediction. We show that our general framework is applicable to other light pollution problems, such as descattering.
doi:10.1145/2077451.2077460 dblp:conf/apgv/BaarPJNTG11 fatcat:wnoiusaucfbarme5d5xeqnb4ku