Reconstruction from non-uniform samples: A direct, variational approach in shift-invariant spaces
Résumé
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 de- pendent; 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.
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