  In this paper, we consider the problem of reconstructing piecewise smooth
functions to high accuracy from nonuniform samples of their Fourier transform.
We use the framework of nonuniform generalized sampling (NUGS) to do this, and
to ensure high accuracy we employ reconstruction spaces consisting of splines
or (piecewise) polynomials. We analyze the relation between the dimension of
the reconstruction space and the bandwidth of the nonuniform samples, and show
that it is linear for splines and piecewise polynomials of fixed degree, and
quadratic for piecewise polynomials of varying degree.
