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.
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页码：53 / 81
页数：28
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