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Foundations of Computational Mathematics

Erschienen in:

01.02.2014

Target Identification Using Dictionary Matching of Generalized Polarization Tensors

verfasst von: Habib Ammari, Thomas Boulier, Josselin Garnier, Wenjia Jing, Hyeonbae Kang, Han Wang

Erschienen in: Foundations of Computational Mathematics | Ausgabe 1/2014

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Abstract

The aim of this paper is to provide a fast and efficient procedure for (real-time) target identification in imaging based on matching on a dictionary of precomputed generalized polarization tensors (GPTs). The approach is based on some important properties of the GPTs and new invariants. A new shape representation is given and numerically tested in the presence of measurement noise. The stability and resolution of the proposed identification algorithm is numerically quantified. We compare the proposed GPT-based shape representation with a moment-based one.

Vorheriger Artikel The Magnus Expansion, Trees and Knuth’s Rotation Correspondence

Nächster Artikel Restricted Normal Cones and Sparsity Optimization with Affine Constraints

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Titel: Target Identification Using Dictionary Matching of Generalized Polarization Tensors
verfasst von: Habib Ammari
Thomas Boulier
Josselin Garnier
Wenjia Jing
Hyeonbae Kang
Han Wang
Publikationsdatum: 01.02.2014
Verlag: Springer US
Erschienen in: Foundations of Computational Mathematics / Ausgabe 1/2014
Print ISSN: 1615-3375
Elektronische ISSN: 1615-3383
DOI: https://doi.org/10.1007/s10208-013-9168-6

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