TY - JOUR
T1 - Data dependent triangulations for piecewise linear interpolation
AU - Dyn, Nira
AU - Levin, David
AU - Rippa, Samuel
PY - 1990/1
Y1 - 1990/1
N2 - Given a set of data points in R2 and corresponding data values, it is clear that the quality of a piecewise linear interpolation over triangles depends on the specific triangulation of the data points. While conventional triangulation methods depend only on the distribution of the data points in R2 in this paper we suggest that the triangulation should depend on the data values as well. Several data dependent criteria for defining the triangulation are discussed and efficient algorithms for computing these triangulations are presented. It is shown for a variety of test cases that data dependent triangulations can improve significantly the quality of approximation and that long and thin triangles, which are traditionally avoided, are sometimes very suitable.
AB - Given a set of data points in R2 and corresponding data values, it is clear that the quality of a piecewise linear interpolation over triangles depends on the specific triangulation of the data points. While conventional triangulation methods depend only on the distribution of the data points in R2 in this paper we suggest that the triangulation should depend on the data values as well. Several data dependent criteria for defining the triangulation are discussed and efficient algorithms for computing these triangulations are presented. It is shown for a variety of test cases that data dependent triangulations can improve significantly the quality of approximation and that long and thin triangles, which are traditionally avoided, are sometimes very suitable.
UR - http://www.scopus.com/inward/record.url?scp=0000925756&partnerID=8YFLogxK
U2 - 10.1093/imanum/10.1.137
DO - 10.1093/imanum/10.1.137
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AN - SCOPUS:0000925756
SN - 0272-4979
VL - 10
SP - 137
EP - 154
JO - IMA Journal of Numerical Analysis
JF - IMA Journal of Numerical Analysis
IS - 1
ER -