Random sampling over locally compact Abelian Groups and inversion of the radon transform

Abstract

We consider the problem of reconstructing a measurable function over a Locally Compact Abelian group G from random measurements. The results presented herein are partially inspired by the concept of alias-free sampling. Here, the sampling and interpolation operation is modelled as an approximate convolution operator with respect to a stochastic integral defined with an appropriately chosen random measure. In particular, this includes the case where the random sampling points are chosen accordingly to a Poisson random point process. We provide sufficient conditions that guarantee an approximate reconstruction through a sampling process that is similar to alias-free random sampling. These results are applied to the problem of approximating the inverse Radon transform of a function.