Approximate Image Reconstruction in Landscape Reflection Imaging

Simple reflection imaging of landscape (scenery or extended objects) poses the inverse problem of reconstructing the landscape reflectivity function from its integrals on some particular family of spheres. Such data acquisition is encoded in the framework of a Radon transform on this family of spher...

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Main Authors: Rémi Régnier, Gaël Rigaud, Maï K. Nguyen
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/268295
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spelling doaj-2aeb8e9390a04e4799612eee4f803b0c2020-11-24T20:50:54ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/268295268295Approximate Image Reconstruction in Landscape Reflection ImagingRémi Régnier0Gaël Rigaud1Maï K. Nguyen2Laboratoire Equipes de Traitement de l’Information et Systèmes (ETIS), ENSEA/Université de Cergy-Pontoise/CNRS UMR 8051, 95302 Cergy-Pontoise, FranceInstitute of Applied Mathematics, University of Saarland, 66041 Saarbrücken, GermanyLaboratoire Equipes de Traitement de l’Information et Systèmes (ETIS), ENSEA/Université de Cergy-Pontoise/CNRS UMR 8051, 95302 Cergy-Pontoise, FranceSimple reflection imaging of landscape (scenery or extended objects) poses the inverse problem of reconstructing the landscape reflectivity function from its integrals on some particular family of spheres. Such data acquisition is encoded in the framework of a Radon transform on this family of spheres. In spite of the existence of an exact inversion formula, the numerical landscape reflectivity function reconstitution is best obtained with an approximate but judiciously chosen reconstruction kernel. We describe the working of this reflection imaging modality and its theoretical handling, introduce an efficient and stable image reconstruction algorithm, and present simulation results to prove the validity of this choice as well as to demonstrate the feasibility of this imaging process.http://dx.doi.org/10.1155/2015/268295
collection DOAJ
language English
format Article
sources DOAJ
author Rémi Régnier
Gaël Rigaud
Maï K. Nguyen
spellingShingle Rémi Régnier
Gaël Rigaud
Maï K. Nguyen
Approximate Image Reconstruction in Landscape Reflection Imaging
Mathematical Problems in Engineering
author_facet Rémi Régnier
Gaël Rigaud
Maï K. Nguyen
author_sort Rémi Régnier
title Approximate Image Reconstruction in Landscape Reflection Imaging
title_short Approximate Image Reconstruction in Landscape Reflection Imaging
title_full Approximate Image Reconstruction in Landscape Reflection Imaging
title_fullStr Approximate Image Reconstruction in Landscape Reflection Imaging
title_full_unstemmed Approximate Image Reconstruction in Landscape Reflection Imaging
title_sort approximate image reconstruction in landscape reflection imaging
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description Simple reflection imaging of landscape (scenery or extended objects) poses the inverse problem of reconstructing the landscape reflectivity function from its integrals on some particular family of spheres. Such data acquisition is encoded in the framework of a Radon transform on this family of spheres. In spite of the existence of an exact inversion formula, the numerical landscape reflectivity function reconstitution is best obtained with an approximate but judiciously chosen reconstruction kernel. We describe the working of this reflection imaging modality and its theoretical handling, introduce an efficient and stable image reconstruction algorithm, and present simulation results to prove the validity of this choice as well as to demonstrate the feasibility of this imaging process.
url http://dx.doi.org/10.1155/2015/268295
work_keys_str_mv AT remiregnier approximateimagereconstructioninlandscapereflectionimaging
AT gaelrigaud approximateimagereconstructioninlandscapereflectionimaging
AT maiknguyen approximateimagereconstructioninlandscapereflectionimaging
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