Thinning Algorithms in Scattered Data Modelling

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...

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.

Adaptive Thinning for Terrain Modelling and Image Compression

Adaptive thinning algorithms are greedy point removal schemes for bivariate scattered data sets with corresponding function values, where the points are recursively removed according to some data-dependent criterion. Each subset of points, together with its function values, defines a linear spline over its Delaunay triangulation. The basic criterion for the removal of the next point is to minim...

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.

Thinning Algorithms in Scattered Data