dc.contributor.author | Matkovic, Kresimir | en_US |
dc.contributor.author | Neumann, László | en_US |
dc.contributor.author | Neumann, Attila | en_US |
dc.contributor.author | Psik, Thomas | en_US |
dc.contributor.author | Purgathofer, Werner | en_US |
dc.contributor.editor | Laszlo Neumann and Mateu Sbert and Bruce Gooch and Werner Purgathofer | en_US |
dc.date.accessioned | 2013-10-22T07:40:24Z | |
dc.date.available | 2013-10-22T07:40:24Z | |
dc.date.issued | 2005 | en_US |
dc.identifier.isbn | 3-905673-27-4 | en_US |
dc.identifier.issn | 1816-0859 | en_US |
dc.identifier.uri | http://dx.doi.org/10.2312/COMPAESTH/COMPAESTH05/159-167 | en_US |
dc.description.abstract | Contrast in image processing is usually defined as a ratio between the darkest and the brightest spots of an image. In this paper we introduce a different contrast definition. The newly introduced Global Contrast Factor (GCF) corresponds closer to the human perception of contrast. GCF uses contrasts at various resolution levels in order to compute overall contrast. Experiments were conducted in order to find weight factors needed to calculate GCF. GCF measures richness of detail as perceived by a human observer, and as such can be used in various application areas like rendering, tone mapping, volume visualization, and lighting design. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.title | Global Contrast Factor - a New Approach to Image Contrast | en_US |
dc.description.seriesinformation | Computational Aesthetics in Graphics, Visualization and Imaging | en_US |