 |
Sparse signal recovery from sparsely corrupted measurements
Authors
Christoph Studer, Patrick Kuppinger, Graeme Pope, and Helmut BölcskeiReference
Proc. of IEEE International Symposium on Information Theory (ISIT), St. Petersburg, Russia, pp. 1422-1426, Aug. 2011
DOI: 10.1109/ISIT.2011.6033774
[BibTeX, LaTeX, and HTML Reference] Abstract
We investigate the recovery of signals exhibiting
a sparse representation in a general (i.e., possibly redundant
or incomplete) dictionary that are corrupted by additive noise
admitting a sparse representation in another general dictionary.
This setup covers a wide range of applications, such as image
inpainting, super-resolution, signal separation, and the recovery
of signals that are corrupted by, e.g., clipping, impulse noise,
or narrowband interference. We present deterministic recovery
guarantees based on a recently developed uncertainty relation
and provide corresponding recovery algorithms. The recovery
guarantees we find depend on the signal and noise sparsity levels,
on the coherence parameters of the involved dictionaries, and on
the amount of prior knowledge on the support sets of signal and
noise.Keywords
Sparse signal recovery, compressed sensing, uncertainty relations
Download this document:
 Copyright Notice: © 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
|
