On sparsity averaging

Дата и время публикации : 2013-07-04T14:49:03Z

Авторы публикации и институты :
Rafael E. Carrillo
Jason D. McEwen
Yves Wiaux

Ссылка на журнал-издание: Ссылка на журнал-издание не найдена
Коментарии к cтатье: 4 pages, 3 figures, Proceedings of 10th International Conference on Sampling Theory and Applications (SampTA), Code available at https://github.com/basp-group/sopt, Full journal letter available at http://arxiv.org/abs/arXiv:1208.2330
Первичная категория: cs.IT

Все категории : cs.IT, astro-ph.IM, math.IT

Краткий обзор статьи: Recent developments in Carrillo et al. (2012) and Carrillo et al. (2013) introduced a novel regularization method for compressive imaging in the context of compressed sensing with coherent redundant dictionaries. The approach relies on the observation that natural images exhibit strong average sparsity over multiple coherent frames. The associated reconstruction algorithm, based on an analysis prior and a reweighted $ell_1$ scheme, is dubbed Sparsity Averaging Reweighted Analysis (SARA). We review these advances and extend associated simulations establishing the superiority of SARA to regularization methods based on sparsity in a single frame, for a generic spread spectrum acquisition and for a Fourier acquisition of particular interest in radio astronomy.

Category: Physics