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Cite or link to this item using this URL: http://hdl.handle.net/10182/1011

Title: Constrained visualization using the Shepard Interpolation Family
Author: Brodlie, K. W.
Asim, M. R.
Unsworth, Keith
Date: Dec-2003
Publisher: Lincoln University. Applied Computing, Mathematics and Statistics Group.
Series/Report no.: Research report (Lincoln University (Canterbury, N.Z.). Applied Computing, Mathematics and Statistics Group) ; no. 09/2003
Item Type: Monograph
Abstract: This paper discusses the problem of visualizing data where there are underlying constraints that must be preserved. For example, we may know that the data is inherently positive. We show how the Modified Quadratic Shepard method, which interpolates scattered data of any dimensionality, can be constrained to preserve positivity. We do this by forcing the quadratic basis functions to be positive. The method can be extended to handle other types of contraints, including lower bound of 0 and upper bound of 1, as occurs with fractional data. A further extension allows general range restrictions, creating an interpolant that lies between any two specified functions as the lower and upper bounds.
Persistent URL (URI): http://hdl.handle.net/10182/1011
ISSN: 1174-6696
Appears in Collections:Applied Computing Research Report series

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