  In this paper we analyze two-dimensional wavelet reconstructions from Fourier
samples within the framework of generalized sampling. For this, we consider
both separable compactly-supported wavelets and boundary wavelets. We prove
that the number of samples that must be acquired to ensure a stable and
accurate reconstruction scales linearly with the number of reconstructing
wavelet functions. We also provide numerical experiments that corroborate our
theoretical results.
