Local hybrid approximation for scattered data fitting with bivariate splines

Oleg Davydov, Rossana Morandi, Alessandra Sestini

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

We suggest a local hybrid approximation scheme based on polynomials and radial basis functions, and use it to improve the scattered data fitting algorithm of (Davydov, O., Zeilfelder, F., 2004. Scattered data fitting by direct extension of local polynomials to bivariate splines. Adv. Comp. Math. 21, 223-271). Similar to that algorithm, the new method has linear computational complexity and is therefore suitable for large real world data. Numerical examples suggest that it can produce high quality artifact-free approximations that are more accurate than those given by the original method where pure polynomial local approximations are used. (C) 2006 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)703-721
Number of pages19
JournalComputer Aided Geometric Design
Volume23
Issue number9
DOIs
Publication statusPublished - Dec 2006

Keywords

  • scattered data fitting
  • bivariate splines
  • radial basis functions
  • thin plate spines
  • interpolation
  • polynomials

Fingerprint Dive into the research topics of 'Local hybrid approximation for scattered data fitting with bivariate splines'. Together they form a unique fingerprint.

  • Cite this