Multi-dimensional sparse structured signal approximation using split Bregman iterations

03/21/2013

∙

by   Yoann Isaac, et al.

∙

0

∙

share

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 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.