Approximating Functions From Sampled Fourier Data Using Spline Pseudofilters

Recently, new polynomial approximation formulas were proposed for the reconstruction of compactly supported piecewise smooth functions from Fourier data. Formulas for zero and first degree polynomials were presented. For higher degree approximations, polynomial formulas become extremely complicated to be handled. In this paper we solve this problem by introducing spline approximations. The new approach can be used in the same way as the polynomial one but producing computable formulas for any degree of approximation in Fourier reconstruction. We present general error estimates and numerical experiments.