• The KIPS Transactions:PartA
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• v.13A no.3 s.100
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• pp.267-274
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• 2006

This paper describes a method to achieve different level of detail for the given volumetric data by assigning weight for the given data points. The relation between wavelet transformation and alpha shape was investigated to define the different level of resolution. Scattered data are defined as a collection of data that have little specified connectivity between data points. The quality of interpolant in volumetric trivariate space depends not only on the distribution of the data points in ${\Re}^3$, but also on the data value (intensity). We can improve the quality of an approximation by using wavelet coefficient as weight for the corresponding data points.

• Journal of the Korea Computer Graphics Society
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• v.2 no.2
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• pp.11-20
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• 1996

The numerous application of scattered data include the modeling and visualization of physical phenomena. A tetrahedrization is one of pre-processing steps for 4-D surface interpolation. In this paper, various tetrahedrization methods are discussed including, Delaunay, least squares fitting, gradient difference, and jump in normal direction derivatives. This paper discriminates the characteristics of tetrahedrization through visualizing tetrahedral domain. This paper also, provides the tool that can compare and analyze the quality of 4-D space approximation over tetrahedral domain numerically, as well as graphically.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1553-1567
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• 1996

The numerous applications surface interpolation include the modeling and visualization phenomena. A tetrahedrization is one of pre-processing steps for 4-D space interpolation. The quality of a piecewise linear interpolation 4-D space depends not only on the distribution of the data points in $R^2$, but also on the data values. We show that the quality of approximation can be improved by data dependent tetraheadrization through visualization of 4-D space. This paper discusses Delaunary tetrahedrization method(sphere criterion) and one of the data dependent tetrahedrization methods(least squares fitting criterion). This paper also discusses new data dependent criteria:1) gradient difference, and 2) jump in normal direction derivative.