eprintid: 917
rev_number: 8
eprint_status: archive
userid: 13
dir: disk0/00/00/09/17
datestamp: 2025-06-01 18:45:20
lastmod: 2025-06-01 18:45:20
status_changed: 2025-06-01 18:45:20
type: monograph
metadata_visibility: show
creators_name: SALUCCI, Marco
creators_name: POLI, Lorenzo
creators_name: ZARDI, Francesco
creators_name: TOSI, Luca
creators_name: LUSA, Samantha
creators_name: MASSA, Andrea
creators_id: marco.salucci@unitn.it
creators_id: lorenzo.poli@unitn.it
creators_id: francesco.zardi@eledia.org
creators_id: luca.tosi@unitn.it
creators_id: samantha.lusa@eledia.org
creators_id: andrea.massa@unitn.it
title: Bayesian Compressive Sensing in Multi-Resolution Contrast Source Estimation
ispublished: pub
subjects: AWC
subjects: MCS
full_text_status: public
monograph_type: technical_report
keywords: microwave imaging (MI), contrast source inversion (CSI), Bayesian compressive sensing (BCS), inverse scattering (IS)
abstract: This work proposes a sophisticated multi-step inverse scattering strategy within the contrast source inversion (CSI) framework to reconstruct non-Born scatterers. It adopts a multi-resolution (MR) scheme to represent contrast sources, which are iteratively estimated using a Bayesian compressive sensing (BCS) algorithm that encourages sparse solutions. The method's accuracy and stability are confirmed through extensive testing. Benchmark comparisons demonstrate the approach’s strong performance relative to contemporary advanced techniques.
date: 2025
publisher: ELEDIA Research Center - University of Trento
referencetext: [1] G. Oliveri, M. Salucci, N. Anselmi, and A. Massa, “Compressive sensing as applied to inverse problems for imaging: theory, applications, current trends, and open challenges,” IEEE Antennas Propag. Mag. - Special Issue on “Electromagnetic Inverse Problems for Sensing and Imaging,” vol. 59, no. 5, pp. 34-46, Oct. 2017 (DOI: 10.1109/MAP.2017.2731204).

[2] A. Massa, P. Rocca, and G. Oliveri, “Compressive sensing in electromagnetics - A review,” IEEE Antennas and Propagation Magazine, pp. 224-238, vol. 57, no. 1, Feb. 2015 (DOI: 10.1109/MAP.2015.2397092).

[3] A. Massa and F. Texeira, Guest-Editorial: Special Cluster on Compressive Sensing as Applied to Electromagnetics, IEEE Antennas Wireless Propag. Lett., vol. 14, pp. 1022-1026, 2015 (DOI: 10.1109/LAWP.2015.2425011).

[4] M. Salucci, L. Poli, F. Zardi, L. Tosi, S. Lusa, and A. Massa, ‘Contrast source inversion of sparse targets through multi-resolution Bayesian compressive sensing’, Inverse Probl., vol. 40, no. 5, p. 055016, May 2024 (DOI 10.1088/1361-6420/ad3b33).

[5] G. Oliveri, N. Anselmi, M. Salucci, L. Poli, and A. Massa, “Compressive sampling-based scattering data acquisition in microwave imaging,” J. Electromagn. Waves Appl. J, vol. 37, no. 5, 693–729, Mar. 2023 (DOI: 10.1080/09205071.2023.2188263).

[6] G. Oliveri, L. Poli, N. Anselmi, M. Salucci, and A. Massa, “Compressive sensing-based Born iterative method for tomographic imaging,” IEEE Tran. Microw. Theory Techn., vol. 67, no. 5, pp. 1753-1765, May 2019 (DOI: 10.1109/TMTT.2019.2899848).

[7] M. Salucci, L. Poli, and G. Oliveri, “Full-vectorial 3D microwave imaging of sparse scatterers through a multi-task Bayesian compressive sensing approach,” Journal of Imaging, vol. 5, no. 1, pp. 1-24, Jan. 2019 (DOI: 10.3390/jimaging5010019).

[8] M. Salucci, A. Gelmini, L. Poli, G. Oliveri, and A. Massa, “Progressive compressive sensing for exploiting frequency-diversity in GPR imaging,” J. Electromagn. Waves Appl. J, vol. 32, no. 9, pp. 1164-1193, 2018 (DOI: 10.1080/09205071.2018.1425160).

[9] N. Anselmi, L. Poli, G. Oliveri, and A. Massa, “Iterative multi-resolution bayesian CS for microwave imaging,” IEEE Trans. Antennas Propag., vol. 66, no. 7, pp. 3665-3677, Jul. 2018 (DOI: 10.1109/TAP.2018.2826574).

[10] N. Anselmi, G. Oliveri, M. A. Hannan, M. Salucci, and A. Massa, “Color compressive sensing imaging of arbitrary-shaped scatterers,” IEEE Trans. Microw. Theory Techn., vol. 65, no. 6, pp. 1986-1999, Jun. 2017 (DOI: 10.1109/TMTT.2016.2645570).

[11] N. Anselmi, G. Oliveri, M. Salucci, and A. Massa, “Wavelet-based compressive imaging of sparse targets,” IEEE Trans. Antennas Propag., vol. 63, no. 11, pp. 4889-4900, Nov. 2015 (DOI: 10.1109/TAP.2015.2444423).

[12] G. Oliveri, P.-P. Ding, and L. Poli “3D crack detection in anisotropic layered media through a sparseness-regularized solver,” IEEE Antennas Wireless Propag. Lett., vol. 14, pp. 1031-1034, 2015 (DOI: 10.1109/LAWP.2014.2365523).

[13] L. Poli, G. Oliveri, P.-P. Ding, T. Moriyama, and A. Massa, “Multifrequency Bayesian compressive sensing methods for microwave imaging,” J. Opt. Soc. Am. A, vol. 31, no. 11, pp. 2415-2428, 2014 (DOI: 10.1364/JOSAA.31.002415).

[14] G. Oliveri, N. Anselmi, and A. Massa, “Compressive sensing imaging of non-sparse 2D scatterers by a total-variation approach within the Born approximation,” IEEE Trans. Antennas Propag., vol. 62, no. 10, pp. 5157-5170, Oct. 2014 (DOI: 10.1109/TAP.2014.2344673).
citation:   SALUCCI, Marco and POLI, Lorenzo and ZARDI, Francesco and TOSI, Luca and LUSA, Samantha and MASSA, Andrea  (2025) Bayesian Compressive Sensing in Multi-Resolution Contrast Source Estimation.  Technical Report. ELEDIA Research Center - University of Trento.     
document_url: http://www.eledia.org/students-reports/917/1/Bayesian_Compressive_Sensing_in_Multi-Resolution_Contrast_Source_Estimation.pdf