Edge Adaptive and Energy Preserving Volume Upscaling for High Quality Volume Rendering

dc.contributor.authorGiachetti, Andreaen_US
dc.contributor.authorGuitiƔn, J. A. Iglesiasen_US
dc.contributor.authorGobbetti, Enricoen_US
dc.contributor.editorEnrico Puppo and Andrea Brogni and Leila De Florianien_US
dc.date.accessioned2014-01-27T16:34:07Z
dc.date.available2014-01-27T16:34:07Z
dc.date.issued2010en_US
dc.description.abstractWe 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 dataen_US
dc.description.seriesinformationEurographics Italian Chapter Conference 2010en_US
dc.identifier.isbn978-3-905673-80-7en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2010/017-023en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.4.3 [Image Processing and Computer Vision]: Enhancement/ Sharpening and deblurringen_US
dc.titleEdge Adaptive and Energy Preserving Volume Upscaling for High Quality Volume Renderingen_US
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