In this paper, a new approach based on the Bayesian compressive sampling (BCS ) and within the contrast source formulation of an inverse scattering problem is proposed for imaging sparse scatterers. By enforcing a probabilistic hierarchical prior as a sparsity regularization constraint, the problem is solved by means of a fast relevance vector machine. The effectiveness and robustness of the BCS-based approach are assessed through a set of numerical experiments concerned with various scatterer configurations and different noisy conditions.
Titolo: | A bayesian compressive sampling-based inversion for imaging sparse scatterers |
Autori: | Oliveri, Giacomo; Rocca, Paolo; Massa, Andrea |
Autori Unitn: | |
Titolo del periodico: | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING |
Anno di pubblicazione: | 2011 |
Numero e parte del fascicolo: | 10 |
Codice identificativo Scopus: | 2-s2.0-80053563269 |
Codice identificativo ISI: | WOS:000296889000015 |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/TGRS.2011.2128329 |
Handle: | http://hdl.handle.net/11572/89698 |
Appare nelle tipologie: | 03.1 Articolo su rivista (Journal article) |
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