Reconstruction from non-uniform samples: A direct, variational approach in shift-invariant spaces

We propose a new approach for signal reconstruction from non-uniform samples, without any constraint on their locations. We look for a function that minimizes a classical regularized least-squares criterion, but with the additional constraint that the solution lies in a chosen linear shift-invariant space—typically, a spline space. In comparison with a pure variational treatment involving radial basis functions, our approach is resolution dependent; an important feature for many applications. Moreover, the solution can be computed exactly by a fast non-iterative algorithm, that exploits at best the particular structure of the problem.