Journal article

Scattered data fitting by direct extension of local polynomials to bivariate splines


Authors listDavydov, O; Zeilfelder, F

Publication year2004

Pages223-271

JournalAdvances in Computational Mathematics

Volume number21

Issue number3-4

ISSN1019-7168

eISSN1572-9044

Open access statusGreen

DOI Linkhttps://doi.org/10.1023/B:ACOM.0000032041.68678.fa

PublisherSpringer


Abstract
We present a new scattered data fitting method, where local approximating polynomials are directly extended to smooth (C-1 or C-2) splines on a uniform triangulation Delta ( the four-directional mesh). The method is based on designing appropriate minimal determining sets consisting of whole triangles of domain points for a uniformly distributed subset of Delta. This construction allows to use discrete polynomial least squares approximations to the local portions of the data directly as parts of the approximating spline. The remaining Bernstein-Bezier coefficients are efficiently computed by extension, i.e., using the smoothness conditions. To obtain high quality local polynomial approximations even for difficult point constellations (e.g., with voids, clusters, tracks), we adaptively choose the polynomial degrees by controlling the smallest singular value of the local collocation matrices. The computational complexity of the method grows linearly with the number of data points, which facilitates its application to large data sets. Numerical tests involving standard benchmarks as well as real world scattered data sets illustrate the approximation power of the method, its efficiency and ability to produce surfaces of high visual quality, to deal with noisy data, and to be used for surface compression.



Citation Styles

Harvard Citation styleDavydov, O. and Zeilfelder, F. (2004) Scattered data fitting by direct extension of local polynomials to bivariate splines, Advances in Computational Mathematics, 21(3-4), pp. 223-271. https://doi.org/10.1023/B:ACOM.0000032041.68678.fa

APA Citation styleDavydov, O., & Zeilfelder, F. (2004). Scattered data fitting by direct extension of local polynomials to bivariate splines. Advances in Computational Mathematics. 21(3-4), 223-271. https://doi.org/10.1023/B:ACOM.0000032041.68678.fa



Keywords


APPROXIMATION ORDERBernstein-Bezier techniquesbivariate splinesdimensionFINITE-ELEMENTSfour-directional meshLAGRANGE INTERPOLATIONlocal polynomial least squares approximationminimal determining setscattered data fittingSPACES

Last updated on 2025-10-06 at 09:31