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

被引：0

作者：

Yohann De Castro

Vincent Duval

Romain Petit

机构：

[1] École Centrale de Lyon,Institut Camille Jordan, CNRS UMR 5208

[2] Université Paris-Dauphine,CEREMADE, CNRS, UMR 7534

[3] PSL University,undefined

[4] INRIA-Paris,undefined

[5] MOKAPLAN,undefined

来源：

Journal of Mathematical Imaging and Vision | 2023年 / 65卷

关键词：

Off-the-grid imaging; Inverse problems; Total variation;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

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.

引用

页码：53 / 81

页数：28

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