Edge Adaptive and Energy Preserving Volume Upscaling for High Quality Volume Rendering
| dc.contributor.author | Giachetti, Andrea | en_US |
| dc.contributor.author | GuitiƔn, J. A. Iglesias | en_US |
| dc.contributor.author | Gobbetti, Enrico | en_US |
| dc.contributor.editor | Enrico Puppo and Andrea Brogni and Leila De Floriani | en_US |
| dc.date.accessioned | 2014-01-27T16:34:07Z | |
| dc.date.available | 2014-01-27T16:34:07Z | |
| dc.date.issued | 2010 | en_US |
| dc.description.abstract | We describe an edge-directed optimization-based method for volumetric data supersampling. The method is based on voxel splitting and iterative refinement performed with a greedy optimization driven by the smoothing of second order gray level derivatives and the assumption that the average gray level in the original voxels region cannot change. Due to these assumptions, the method, which is the 3D extension of a recently proposed technique, is particularly suitable for upscaling medical imaging data creating physically reasonable voxel values and overcoming the so-called partial volume effect. The good quality of the results obtained is demonstrated through experimental tests. Furthermore, we show how offline 3D upscaling of volumes can be coupled with recent techniques to perform high quality volume rendering of large datasets, obtaining a better inspection of medical volumetric data | en_US |
| dc.description.seriesinformation | Eurographics Italian Chapter Conference 2010 | en_US |
| dc.identifier.isbn | 978-3-905673-80-7 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2010/017-023 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Categories and Subject Descriptors (according to ACM CCS): I.4.3 [Image Processing and Computer Vision]: Enhancement/ Sharpening and deblurring | en_US |
| dc.title | Edge Adaptive and Energy Preserving Volume Upscaling for High Quality Volume Rendering | en_US |
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