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Local ambient occlusion in direct volume rendering
Linköping University, Department of Science and Technology, Media and Information Technology.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. (Immersive Visualization)ORCID iD: 0000-0002-9288-5322
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-9466-9826
2010 (English)In: Visualization and Computer Graphics, IEEE Transactions on, ISSN 1077-2626, Vol. 16, no 4, 548-559 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel technique to efficiently compute illumination for Direct Volume Rendering using a local approximation of ambient occlusion to integrate the intensity of incident light for each voxel. An advantage with this local approach is that fully shadowed regions are avoided, a desirable feature in many applications of volume rendering such as medical visualization.

Additional transfer function interactions are also presented, for instance, to highlight specific structures with luminous tissue effects and create an improved context for semitransparent tissues with a separate absorption control for the illumination settings. Multiresolution volume management and GPU-based computation are used to accelerate the calculations and support large data sets. The scheme yields interactive frame rates with an adaptive sampling approach for incrementally refined illumination under arbitrary transfer function changes. The illumination effects can give a better understanding of the shape and density of tissues and so has the potential to increase the diagnostic value of medical volume rendering. Since the proposed method is gradient-free, it is especially beneficial at the borders of clip planes, where gradients are undefined, and for noisy data sets.

Place, publisher, year, edition, pages
2010. Vol. 16, no 4, 548-559 p.
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-119033DOI: 10.1109/TVCG.2009.45OAI: oai:DiVA.org:liu-119033DiVA: diva2:820171
Available from: 2015-06-11 Created: 2015-06-08 Last updated: 2015-06-30

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Ljung, PatricYnnerman, Anders
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