Papers › Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems
Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems
Yohann de Castro, Vincent Duval, Romain Petit
We introduce an algorithm to solve linear inverse problems regularized with the total (gradient) variation in a gridless manner. Contrary to most existing methods, that produce an approximate solution which is piecewise constant on a fixed mesh, our approach exploits the structure of the solutions and consists in iteratively constructing a linear combination of indicator functions of simple polygons.
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