Multispectral Image Feature Points

Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized usin...

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Detalles Bibliográficos
Autores principales: Aguilera, Cristhian, Barrera, Fernando, Lumbreras, Felipe, Sappa, Angel D., Toledo, Ricardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3478863/
http://dx.doi.org/10.3390/s120912661
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author Aguilera, Cristhian
Barrera, Fernando
Lumbreras, Felipe
Sappa, Angel D.
Toledo, Ricardo
author_facet Aguilera, Cristhian
Barrera, Fernando
Lumbreras, Felipe
Sappa, Angel D.
Toledo, Ricardo
author_sort Aguilera, Cristhian
collection PubMed
description Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.
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spelling pubmed-34788632012-10-30 Multispectral Image Feature Points Aguilera, Cristhian Barrera, Fernando Lumbreras, Felipe Sappa, Angel D. Toledo, Ricardo Sensors (Basel) Article Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. Molecular Diversity Preservation International (MDPI) 2012-09-17 /pmc/articles/PMC3478863/ http://dx.doi.org/10.3390/s120912661 Text en © 2012 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 license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Aguilera, Cristhian
Barrera, Fernando
Lumbreras, Felipe
Sappa, Angel D.
Toledo, Ricardo
Multispectral Image Feature Points
title Multispectral Image Feature Points
title_full Multispectral Image Feature Points
title_fullStr Multispectral Image Feature Points
title_full_unstemmed Multispectral Image Feature Points
title_short Multispectral Image Feature Points
title_sort multispectral image feature points
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3478863/
http://dx.doi.org/10.3390/s120912661
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