Adaptive thinning for bivariate scattered data

Adaptive Thinning for Bivariate Scattered Data

This paper studies adaptive thinning strategies for approximating a large set of scattered data by piecewise linear functions over triangulated subsets. Our strategies depend on both the locations of the data points in the plane, and the values of the sampled function at these points — adaptive thinning. All our thinning strategies remove data points one by one, so as to minimize an estimate of...

Thinning Algorithms in Scattered Data

Thinning algorithms for scattered data interpolation

Multistep interpolation of scattered data by compactly supported radial basis functions requires hierarchical subsets of the data. This paper analyzes thinning algorithms for generating evenly distributed subsets of scattered data in a given domain in IR. AMS subject classification: 41A15, 65D05, 65D07.

Thinning Algorithms in Scattered Data Modelling

Thinning, Inserting, and Swapping Scattered Data

Thinning, insertion, and swapping algorithms for generating well-distributed hierarchical subsets of scattered data in a given domain in IR are proposed. It is found that thinning and insertion yield approximately similar results but that swapping is in general inferior.