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Book Sections Year : 2021

Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems

Abstract

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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Dates and versions

hal-03196916 , version 1 (13-04-2021)
hal-03196916 , version 2 (03-11-2021)

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Yohann de Castro, Vincent Duval, Romain Petit. Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems. Elmoataz, Abderrahim; Fadili, Jalal; Quéau, Yvain; Rabin, Julien; Simon, Loïc. Scale Space and Variational Methods in Computer Vision, 12679, Springer, Cham, pp.553-564, 2021, Lecture Notes in Computer Sciences, ⟨10.1007/978-3-030-75549-2_44⟩. ⟨hal-03196916v2⟩
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