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Journal Articles Journal of Mathematical Imaging and Vision Year : 2022

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-03406710 , version 1 (09-11-2021)
hal-03406710 , version 2 (11-04-2022)
hal-03406710 , version 3 (09-07-2022)

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Cite

Yohann de Castro, Vincent Duval, Romain Petit. Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems. Journal of Mathematical Imaging and Vision, 2022, ⟨10.1007/s10851-022-01115-w⟩. ⟨hal-03406710v3⟩
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