Multistep scattered data interpolation using compactly supported radial basis functions
Journal of Computational and Applied Mathematics - Special issue on scattered data
Shape preserving interpolation by space curves
Computer Aided Geometric Design
Modelling with implicit surfaces that interpolate
ACM Transactions on Graphics (TOG)
Radial basis functions for the multivariate interpolation of large scattered data sets
Journal of Computational and Applied Mathematics - Special issue: Proceedings of the 9th International Congress on computational and applied mathematics
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Radial Basis Functions
3D scattered data interpolation and approximation with multilevel compactly supported RBFs
Graphical Models - Special issue on SMI 2003
Shape preserving spline interpolation
Computer-Aided Design
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In this paper, we present an new approach to construct the so-called shape preserving interpolation curves. The basic idea is first to approximate the set of interpolated points with a class of MQ quasi-interpolation operators and then pass through the set with the use of multivariate interpolation by using compactly supported radial basis functions. This approach possesses the advantages of certain shape preserving and good approximation behaviors. The proposed algorithm is easy to implement.