TY - GEN
T1 - Feature-driven volume fairing
AU - Takahashi, Shigeo
AU - Kobayashi, Jun
AU - Fujishiro, Issei
PY - 2009
Y1 - 2009
N2 - Volume datasets have been a primary representation for scientific visualization with the advent of rendering algorithms such as marching cubes and ray casting. Nonetheless, illuminating the underlying spatial structures still requires careful adjustment of visualization parameters each time when a different dataset is provided. This paper introduces a new framework, called feature-driven volume fairing, which transforms any 3D scalar field into a canonical form to be used as communication media of scientific volume data. The transformation is accomplished by first modulating the topological structure of the volume so that the associated isosurfaces never incur internal voids, and then geometrically elongating the significant feature regions over the range of scalar field values. This framework allows us to elucidate spatial structures in the volume instantly using a predefined set of visualization parameters, and further enables data compression of the volume with a smaller number of quantization levels for efficient data transmission.
AB - Volume datasets have been a primary representation for scientific visualization with the advent of rendering algorithms such as marching cubes and ray casting. Nonetheless, illuminating the underlying spatial structures still requires careful adjustment of visualization parameters each time when a different dataset is provided. This paper introduces a new framework, called feature-driven volume fairing, which transforms any 3D scalar field into a canonical form to be used as communication media of scientific volume data. The transformation is accomplished by first modulating the topological structure of the volume so that the associated isosurfaces never incur internal voids, and then geometrically elongating the significant feature regions over the range of scalar field values. This framework allows us to elucidate spatial structures in the volume instantly using a predefined set of visualization parameters, and further enables data compression of the volume with a smaller number of quantization levels for efficient data transmission.
UR - http://www.scopus.com/inward/record.url?scp=70350663201&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-02115-2_20
DO - 10.1007/978-3-642-02115-2_20
M3 - Conference contribution
AN - SCOPUS:70350663201
SN - 364202114X
SN - 9783642021145
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 233
EP - 242
BT - Smart Graphics - 10th International Symposium, SG 2009, Proceedings
T2 - 10th International Symposium on Smart Graphics, SG 2009
Y2 - 28 May 2009 through 30 May 2009
ER -