Abstract
Since the 1970’s B-splines have evolved to become the {} standard for curve and surface representation due to many of their salient properties. Conventional least-squares scattered data fitting techniques for B-splines require the inversion of potentially large matrices. This is time-consuming as well as susceptible to ill-conditioning which leads to undesired results. Lee {} proposed a novel B-spline algorithm for fitting a 2-D cubic B-spline surface to scattered data in . The proposed algorithm utilizes an optional multilevel approach for better fitting results. We generalize this technique to support N-dimensional data fitting as well as arbitrary degree of B-spline. In addition, we generalize the B-spline kernel function class to accommodate this new image filter.
Keywords
B-splineCurve fittingMathematicsAlgorithmSpline (mechanical)Applied mathematicsComputer scienceMathematical analysisStatisticsPhysics
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Publication Info
- Year
- 2005
- Type
- article
- Citations
- 9
- Access
- Closed
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Cite This
Nicholas J. Tustison,
James C. Gee
(2005).
N-D $C^k$ B-Spline Scattered Data Approximation.
The Insight Journal
.
https://doi.org/10.54294/0d55to
Identifiers
- DOI
- 10.54294/0d55to