@inproceedings{f32e55ee55d443f385002e57d6f2665d,
title = "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.",
keywords = "Inverse problems, Off-the-grid imaging, Total variation",
author = "\{De Castro\}, Yohann and Vincent Duval and Romain Petit",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021 ; Conference date: 16-05-2021 Through 20-05-2021",
year = "2021",
month = jan,
day = "1",
doi = "10.1007/978-3-030-75549-2\_44",
language = "English",
isbn = "9783030755485",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "553--564",
editor = "Abderrahim Elmoataz and Jalal Fadili and Yvain Qu{\'e}au and Julien Rabin and Lo{\"i}c Simon",
booktitle = "Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings",
}