Importance-Driven Feature Enhancement in Volume Visualization

Ivan Viola, Armin Kanitsar, Meister Eduard Gröller
Importance-Driven Feature Enhancement in Volume Visualization
TR-186-2-04-09, September 2004 [ paper]
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Abstract

This paper introduces importance-driven volume rendering as a novel technique for automatic focus and context display of volumetric data. Our technique is a generalization of cut-away views, which -- depending on the viewpoint or feature -- remove or suppress less important parts of a scene to reveal more important underlying information. We automatize and apply this idea to volumetric data.

Each part of the volumetric data is assigned an emph{object importance} which encodes visibility priority. This property determines which structures should be readily discernible and which structures are less important. In those image regions, where an object occludes more important structures it is displayed more sparsely than in those areas where no occlusion occurs. Thus the objects of interest are clearly visible. For each object several representations, i.e., emph{levels of sparseness}, are specified. The display of an individual object may incorporate different levels of sparseness. The goal is to emphasize important structures and to maximize the information content in the final image.

This paper also discusses several possible schemes for emph{level of sparseness} specification and different ways how emph{object importance} can be composited to determine the final appearance of a particular object.

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@techreport{viola-2004-imp,
  title =      "Importance-Driven Feature Enhancement in Volume
               Visualization",
  author =     "Ivan Viola and Armin Kanitsar and Meister Eduard
               Gr{\"o}ller",
  year =       "2004",
  abstract =   "This paper introduces importance-driven volume rendering as
               a novel technique for automatic focus and context display of
               volumetric data. Our technique is a generalization of
               cut-away views, which -- depending on the viewpoint or
               feature -- remove or suppress less important parts of a
               scene to reveal more important underlying information. We
               automatize and apply this idea to volumetric data.  Each
               part of the volumetric data is assigned an emph{object
               importance} which encodes visibility priority. This property
               determines which structures should be readily discernible
               and which structures are less important. In those image
               regions, where an object occludes more important structures
               it is displayed more sparsely than in those areas where no
               occlusion occurs. Thus the objects of interest are clearly
               visible. For each object several representations, i.e.,
               emph{levels of sparseness}, are specified. The display of an
               individual object may incorporate different levels of
               sparseness. The goal is to emphasize important structures
               and to maximize the information content in the final image. 
               This paper also discusses several possible schemes for
               emph{level of sparseness} specification and different ways
               how emph{object importance} can be composited to determine
               the final appearance of a particular object.",
  address =    "Favoritenstrasse 9-11/186, A-1040 Vienna, Austria",
  institution = "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology",
  note =       "human contact: technical-report@cg.tuwien.ac.at",
  month =      sep,
  number =     "TR-186-2-04-09",
  keywords =   "level-of-detail techniques, focus+context techniques, volume
               rendering, view-dependent visualization, non-photorealistic
               techniques",
  URL =        "http://www.cg.tuwien.ac.at/research/publications/2004/viola-2004-imp/",
}