@inbook{dc074c5a071f494baeb397004ffb377b,
title = "Total variation minimization in compressed sensing",
abstract = "This chapter gives an overview over recovery guarantees for total variation minimization in compressed sensing for different measurement scenarios. In addition to summarizing the results in the area, we illustrate why an approach that is common for synthesis sparse signals fails and different techniques are necessary. Lastly, we discuss a generalization of recent results for Gaussian measurements to the subgaussian case.",
keywords = "Compressed sensing, Gradient sparsity, Total variation minimization",
author = "Felix Krahmer and Christian Kruschel and Michael Sandbichler",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.",
year = "2017",
doi = "10.1007/978-3-319-69802-1_11",
language = "English",
series = "Applied and Numerical Harmonic Analysis",
publisher = "Springer International Publishing",
number = "9783319698014",
pages = "333--358",
booktitle = "Applied and Numerical Harmonic Analysis",
edition = "9783319698014",
}