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Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging

Numerous prototypes of computational imaging systems have recently been presented in the microwave and millimeter-wave domains, enabling the simplification of associated active architectures through the use of radiating cavities and metasurfaces that can multiplex signals encoded in the physical lay...

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Detalles Bibliográficos
Autores principales: Fromenteze, Thomas, Decroze, Cyril, Abid, Sana, Yurduseven, Okan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982233/
https://www.ncbi.nlm.nih.gov/pubmed/29757241
http://dx.doi.org/10.3390/s18051536
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author Fromenteze, Thomas
Decroze, Cyril
Abid, Sana
Yurduseven, Okan
author_facet Fromenteze, Thomas
Decroze, Cyril
Abid, Sana
Yurduseven, Okan
author_sort Fromenteze, Thomas
collection PubMed
description Numerous prototypes of computational imaging systems have recently been presented in the microwave and millimeter-wave domains, enabling the simplification of associated active architectures through the use of radiating cavities and metasurfaces that can multiplex signals encoded in the physical layer. This paper presents a new reconstruction technique leveraging the sparsity of the signals in the time-domain and decomposition of the sensing matrix by support detection, the size of the computational inverse problem being reduced significantly without compromising the image quality.
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spelling pubmed-59822332018-06-05 Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging Fromenteze, Thomas Decroze, Cyril Abid, Sana Yurduseven, Okan Sensors (Basel) Article Numerous prototypes of computational imaging systems have recently been presented in the microwave and millimeter-wave domains, enabling the simplification of associated active architectures through the use of radiating cavities and metasurfaces that can multiplex signals encoded in the physical layer. This paper presents a new reconstruction technique leveraging the sparsity of the signals in the time-domain and decomposition of the sensing matrix by support detection, the size of the computational inverse problem being reduced significantly without compromising the image quality. MDPI 2018-05-12 /pmc/articles/PMC5982233/ /pubmed/29757241 http://dx.doi.org/10.3390/s18051536 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fromenteze, Thomas
Decroze, Cyril
Abid, Sana
Yurduseven, Okan
Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging
title Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging
title_full Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging
title_fullStr Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging
title_full_unstemmed Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging
title_short Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging
title_sort sparsity-driven reconstruction technique for microwave/millimeter-wave computational imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982233/
https://www.ncbi.nlm.nih.gov/pubmed/29757241
http://dx.doi.org/10.3390/s18051536
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