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.

Advances in Digital Image Compression by Adaptive Thinning

This paper proposes a novel concept for digital image compression. The resulting compression scheme relies on adaptive thinning algorithms, which are recent multiresolution methods from scattered data approximation. Adaptive thinning algorithms are recursive point removal schemes, which are combined with piecewise linear interpolation over decremental Delaunay triangulations. This paper shows t...

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...