Volume Ray Casting with Peak Finding and Differential Sampling

A. Knoll, Y. Hijazi, R. Westerteiger, M. Schott, C. Hansen, H. Hagen

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


Direct volume rendering and isosurfacing are ubiquitous rendering techniques in scientific visualization, commonly employed in imaging 3D data from simulation and scan sources. Conventionally, these methods have been treated as separate modalities, necessitating different sampling strategies and rendering algorithms. In reality, an isosurface is a special case of a transfer function, namely a Dirac impulse at a given isovalue. However, artifact-free rendering of discrete isosurfaces in a volume rendering framework is an elusive goal, requiring either infinite sampling or smoothing of the transfer function. While preintegration approaches solve the most obvious deficiencies in handling sharp transfer functions, artifacts can still result, limiting classification. In this paper, we introduce a method for rendering such features by explicitly solving for isovalues within the volume rendering integral. In addition, we present a sampling strategy inspired by ray differentials that automatically matches the frequency of the image plane, resulting in fewer artifacts near the eye and better overall performance. These techniques exhibit clear advantages over standard uniform ray casting with and without preintegration, and allow for high-quality interactive volume rendering with sharp C0 transfer functions. © 2009 IEEE.
Original languageEnglish (US)
Pages (from-to)1571-1578
Number of pages8
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number6
StatePublished - Nov 2009
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: This work was supported by the German Research Foundation (DFG)through the University of Kaiserslautern International Research TrainingGroup (IRTG 1131); as well as the National Science Foundationunder grants CNS-0615194, CNS-0551724, CCF-0541113, IIS-0513212, and DOE VACET SciDAC, KAUST GRP KUS-C1-016-04.Additional thanks to Liz Jurrus and Tolga Tasdizen for the zebrafishdata, and to the anonymous reviewers for their comments.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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