A Parallel Implementation of the Triangular Shepard Interpolation Method

Abstract

The triangular Shepard interpolation method is an extension of the well-known bivariate Shepard’s method for interpolating large sets of scattered data. In particular, the classical point-based weight functions are substituted by basis functions built upon triangulation of the scattered points. As shown in the literature, this method exhibits advantages with respect to other interpolation methods for interpolating scattered bivariate data. Nevertheless, as the size of the data set increases, an efficient implementation of the method becomes more and more necessary. In this paper, we present a parallel implementation of the triangular Shepard interpolation method that beside exploiting benefits due to the parallelization itself, introduces a novel approach for the triangulation of the scattered data.