Multi-dimensional sparse structured signal approximation using split bregman iterations
Résumé
The paper focuses on the sparse approximation of signals using overcomplete representations, such that it preserves the (prior) structure of multi-dimensional signals. The underlying optimization problem is tackled using a multi-dimensional extension of the split Bregman optimization approach. An extensive empirical evaluation shows how the proposed approach compares to the state of the art depending on the signal features.
| Origine | Fichiers produits par l'(les) auteur(s) |
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