## Imaging sparse metallic cylinders through a local shape function Bayesian compressive sensing approach |

JOSA A, Vol. 30, Issue 6, pp. 1261-1272 (2013)

http://dx.doi.org/10.1364/JOSAA.30.001261

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### Abstract

An innovative method for the localization of multiple sparse metallic targets is proposed. Starting from the local shape function (LSF) formulation of the inverse scattering problem and exploiting the multitask Bayesian compressive sensing (MT-BCS) paradigm, a two-step approach is described where, after a first estimation of the LSF scattering amplitudes, the reconstruction of the metallic objects is yielded through a thresholding and voting step. Selected numerical examples are presented to analyze the accuracy, the robustness, and the computational efficiency of the LSF–MT-BCS technique.

© 2013 Optical Society of America

**OCIS Codes**

(100.3190) Image processing : Inverse problems

(100.6950) Image processing : Tomographic image processing

(280.0280) Remote sensing and sensors : Remote sensing and sensors

(290.3200) Scattering : Inverse scattering

(350.4010) Other areas of optics : Microwaves

**ToC Category:**

Scattering

**History**

Original Manuscript: February 19, 2013

Manuscript Accepted: May 5, 2013

Published: May 28, 2013

**Virtual Issues**

July 23, 2013 *Spotlight on Optics*

**Citation**

Lorenzo Poli, Giacomo Oliveri, and Andrea Massa, "Imaging sparse metallic cylinders through a local shape function Bayesian compressive sensing approach," J. Opt. Soc. Am. A **30**, 1261-1272 (2013)

http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-30-6-1261

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