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    Volume Ray Casting with Peak Finding and Differential Sampling

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    Type
    Article
    Authors
    Knoll, A.
    Hijazi, Y.
    Westerteiger, R.
    Schott, M.
    Hansen, C.
    Hagen, H.
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2009-11
    Permanent link to this record
    http://hdl.handle.net/10754/600178
    
    Metadata
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    Abstract
    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.
    Citation
    Knoll A, Hijazi Y, Westerteiger R, Schott M, Hansen C, et al. (2009) Volume Ray Casting with Peak Finding and Differential Sampling. IEEE Transactions on Visualization and Computer Graphics 15: 1571–1578. Available: http://dx.doi.org/10.1109/TVCG.2009.204.
    Sponsors
    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.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Visualization and Computer Graphics
    DOI
    10.1109/TVCG.2009.204
    PubMed ID
    19834235
    ae974a485f413a2113503eed53cd6c53
    10.1109/TVCG.2009.204
    Scopus Count
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