Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations

no code implementations • 29 Sep 2016 • Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif

This paper addresses the structurally-constrained sparse decomposition of multi-dimensional signals onto overcomplete families of vectors, called dictionaries.

Multi-dimensional sparse structured signal approximation using split Bregman iterations

no code implementations • 21 Mar 2013 • Yoann Isaac, Quentin Barthélemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag

An extensive empirical evaluation shows how the proposed approach compares to the state of the art depending on the signal features.