relation: http://www.eledia.org/students-reports/917/
title: Bayesian Compressive Sensing in Multi-Resolution Contrast Source Estimation
creator: SALUCCI, Marco
creator: POLI, Lorenzo
creator: ZARDI, Francesco
creator: TOSI, Luca
creator: LUSA, Samantha
creator: MASSA, Andrea
subject: A WC Next Generation Wireless Communications
subject: M CS Compressive Sensing
description: 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.
publisher: ELEDIA Research Center - University of Trento
date: 2025
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/917/1/Bayesian_Compressive_Sensing_in_Multi-Resolution_Contrast_Source_Estimation.pdf
identifier:   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.