Next Article in Journal
Degraded Historical Document Binarization: A Review on Issues, Challenges, Techniques, and Future Directions
Next Article in Special Issue
A Minimum Rank Approach for Reduction of Environmental Noise in Near-Field Array Antenna Diagnosis
Previous Article in Journal
Beyond All-Sky: Assessing Ecological Light Pollution Using Multi-Spectral Full-Sphere Fisheye Lens Imaging
Previous Article in Special Issue
Contraction Integral Equation for Three-Dimensional Electromagnetic Inverse Scattering Problems
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle

Qualitative Methods for the Inverse Obstacle Problem: A Comparison on Experimental Data

1,2,*,† and 1,†
1
DIIES, Department of Information Engineering, Infrastructures and Sustainable Energy, Università Mediterranea di Reggio Calabria, via Graziella, Loc. Feo di Vito, 89124 Reggio Calabria, Italy
2
CNR-IREA, National Research Council of Italy, Institute of Electromagnetic Sensing of the Environment, via Diocleziano 328, 80124 Napoli, Italy
*
Author to whom correspondence should be addressed.
The paper is a result of a joint contribution of both the authors, from conceptualization to final writing and editing.
J. Imaging 2019, 5(4), 47; https://doi.org/10.3390/jimaging5040047
Received: 7 March 2019 / Revised: 29 March 2019 / Accepted: 8 April 2019 / Published: 10 April 2019
(This article belongs to the Special Issue Microwave Imaging and Electromagnetic Inverse Scattering Problems)
  |  
PDF [5269 KB, uploaded 19 April 2019]
  |  

Abstract

Qualitative methods are widely used for the solution of inverse obstacle problems. They allow one to retrieve the morphological properties of the unknown targets from the scattered field by avoiding dealing with the problem in its full non-linearity and considering a simplified mathematical model with a lower computational burden. Very many qualitative approaches have been proposed in the literature. In this paper, a comparison is performed in terms of performance amongst three different qualitative methods, i.e., the linear sampling method, the orthogonality sampling method, and a recently introduced method based on joint sparsity and equivalence principles. In particular, the analysis is focused on the inversion of experimental data and considers a wide range of (distinct) working frequencies and different kinds of scattering experiments. View Full-Text
Keywords: inverse obstacles problem; inverse source problem; joint sparsity; linear sampling method; microwave imaging; orthogonality sampling method inverse obstacles problem; inverse source problem; joint sparsity; linear sampling method; microwave imaging; orthogonality sampling method
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Bevacqua, M.T.; Palmeri, R. Qualitative Methods for the Inverse Obstacle Problem: A Comparison on Experimental Data. J. Imaging 2019, 5, 47.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Imaging EISSN 2313-433X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top