CGAL 4.8.2  2D and Surface Function Interpolation

Scattered data interpolation solves the following problem: given measures of a function on a set of discrete data points, the task is to interpolate this function on an arbitrary query point.
If the function is a linear function and given barycentric coordinates that allow to express the query point as the convex combination of some data points, the function can be exactly interpolated. If the function gradients are known, we can exactly interpolate quadratic functions given barycentric coordinates. Any further properties of these interpolation functions depend on the properties of the barycentric coordinates. They are provided in this package under the name linear_interpolation()
and quadratic_interpolation()
.
Natural neighbor coordinates are defined by Sibson in 1980 and are based on the Voronoi diagram of the data points. Interpolation methods based on natural neighbor coordinates are particularly interesting because they adapt easily to nonuniform and highly anisotropic data. This package contains Sibson's \( C^1\) continuous interpolation method which interpolates exactly spherical quadrics (of the form \( \Phi(\mathbf{x})=a + \mathbf{b}^t \mathbf{x} +\gamma\ \mathbf{x}^t\mathbf{x}\)) and Farin's \( C^1\) continuous interpolation method based on BernsteinBézier techniques and interpolating exactly quadratic functions  assuming that the function gradient is known. In addition, Sibson defines a method to approximate the function gradients for data points that are in the interior of the convex hull. This method is exact for spherical quadrics.
This CGAL package implements Sibson's and Farin's interpolation functions as well as Sibson's function gradient fitting method. Furthermore, it provides functions to compute the natural neighbor coordinates with respect to a twodimensional Voronoi diagram (i. e., from the Delaunay triangulation of the data points) and to a twodimensional power diagram for weighted points (i. e., from their regular triangulation). Natural neighbor coordinates on closed and wellsampled surfaces can also be computed if the normal to the surface at the query point is known. The latter coordinates are only approximately barycentric, see [2].
For a more thorough introduction see the user manual.
CGAL::linear_interpolation
CGAL::sibson_c1_interpolation
CGAL::farin_c1_interpolation
CGAL::quadratic_interpolation
CGAL::sibson_gradient_fitting
CGAL::Interpolation_traits_2<K>
CGAL::Interpolation_gradient_fitting_traits_2<K>
CGAL::Voronoi_intersection_2_traits_3<K>
CGAL::surface_neighbor_coordinates_3
CGAL::surface_neighbors_3
Modules  
Concepts  
Interpolation Functions  
Natural Neighbor Coordinate Computation  
Surface Neighbor and Surface Neighbor Coordinate Computation  
Classes  
struct  CGAL::Data_access< Map > 
The struct Data_access implements a functor that allows to retrieve data from an associative container. More...  