The application of the compressive sensing (CS) paradigm to retrieve non-single-pixels contrast profiles is discussed. By exploiting a wavelet representation to model complex scatterer distributions with sparse vectors of coefficients, an efficient Bayesian CS (BCS) strategy is adopted to solve the arising inverse scattering problem. A set of representative numerical examples is presented to illustrate the advantages and the limitations of the proposed approach also with respect to comparable state-of-the-art inversion methods

Wavelet-based compressive imaging of sparse targets / Anselmi, Nicola; Salucci, Marco; Oliveri, Giacomo; Massa, Andrea. - In: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. - ISSN 0018-926X. - STAMPA. - 63:11(2015), pp. 4889-4900. [10.1109/TAP.2015.2444423]

Wavelet-based compressive imaging of sparse targets

Anselmi, Nicola;Salucci, Marco;Oliveri, Giacomo;Massa, Andrea
2015

Abstract

The application of the compressive sensing (CS) paradigm to retrieve non-single-pixels contrast profiles is discussed. By exploiting a wavelet representation to model complex scatterer distributions with sparse vectors of coefficients, an efficient Bayesian CS (BCS) strategy is adopted to solve the arising inverse scattering problem. A set of representative numerical examples is presented to illustrate the advantages and the limitations of the proposed approach also with respect to comparable state-of-the-art inversion methods
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Anselmi, Nicola; Salucci, Marco; Oliveri, Giacomo; Massa, Andrea
Wavelet-based compressive imaging of sparse targets / Anselmi, Nicola; Salucci, Marco; Oliveri, Giacomo; Massa, Andrea. - In: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. - ISSN 0018-926X. - STAMPA. - 63:11(2015), pp. 4889-4900. [10.1109/TAP.2015.2444423]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/135463
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