Targets Classification on Multispectral Images using Connectionists Methods

Samir Zeriouh; Mustapha Boutahri; Said El Yamani; Ahmed Roukhe

doi:doi:10.11648/j.ajpa.20150303.14

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Targets Classification on Multispectral Images using Connectionists Methods

Samir Zeriouh, Mustapha Boutahri, Said El Yamani, Ahmed Roukhe

Published in American Journal of Physics and Applications (Volume 3, Issue 3)

Received: 4 April 2015 Accepted: 17 April 2015 Published: 27 April 2015

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Abstract

Identification of targets on remote sensing images depends mainly on the databases representing different classes. In this context, this paper proposes a connectionist system using a two-dimensional Kohonen self-organizing map to build a database of some identified targets on a multi-band satellite image. After an enhancing process, essentially based on a non-linear filtering, the system performs a non-supervised classification of a reference image in order to extract the sequence of samples of the reflectance coefficients related to the desired targets. This classification will be used later for automatic extraction of these targets on other stages.

Published in	American Journal of Physics and Applications (Volume 3, Issue 3)
DOI	10.11648/j.ajpa.20150303.14
Page(s)	86-91
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Multispectral Image, Classification, Identification, Artificial Neural Networks, Self-Organizing Map

References

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[2]	H. Guo, J. E. Odegard, M. Lang, R. A. Gopinath, I.W. Selesnick, and C. S. Burrus, “Wavelet based Speckle Reduction with Application to SAR based ATD/R,” First International Conference on Image Processing, 1, 1994, pp. 75-79.
[3]	Maïtine Bergounioux. Quelques méthodes de filtrages en traitement d’image.CIMPA, hal-00512280v1, 2011.
[4]	E. Nezry, Amélioration radiométrique et préservation de la réflectivité radar des images SAR par les filtres de speckle adaptatifs : Théorie et résultats expérimentaux, Centre commun de recherche, Institut des applications de la télédétection, Commission européenne, 1994, pp.3-7.
[5]	J. Philippe, G. Etchegorry, F. Adragna, Y. Kerr, J. Lagouarde, M. Leroy et T. Le Toan, Observation spaciale des paramètres de surface, (Paramètres de surface et signatures spectrales), La télédétection en Francophonie : analyse et perspectives, Edition AUF2000, pp. 299-317.
[6]	N. Allinson, H. Yin, N. Allinson and J. Slack Eds. Self-Organizing Maps.Springer, 2001, pp.95-101.
[7]	T. Kohonen, Essentials of the self-organizing map, Neural Networks 37, 2013, pp. 52–65.
[8]	T. Kohonen, Self-Organizing Maps, Springer Series in Information Sciences, Vol.30, 2°edition, 1997.
[9]	M. Hendel, A. Benyettou, F. Hendel, H. Khilil, « Classification automatique des signaux ECG par les réseaux de neurones probabilistes », "Applications Médicales de l'Informatique : Nouvelles Approches", Monastir-Tunisie, 13, 14 et 15 Novembre 2008.
[10]	R. Le page, Détection et analyse de l’onde P d’un électrocardiogramme : application au dépistage de la fibrillation auriculaire, Thèse Doctorat d’état électronique. L’université de Bretagne occidentale, 2003.
[11]	Teuvo Kohonen, Jussi Hynninen, Jari Kangas and Jorma Laaksonen. Som-pak, the self-organizing map program package. SOM programming team of Helsinki University of Technology, April 1995.

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APA Style

Samir Zeriouh, Mustapha Boutahri, Said El Yamani, Ahmed Roukhe. (2015). Targets Classification on Multispectral Images using Connectionists Methods. American Journal of Physics and Applications, 3(3), 86-91. https://doi.org/10.11648/j.ajpa.20150303.14

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ACS Style

Samir Zeriouh; Mustapha Boutahri; Said El Yamani; Ahmed Roukhe. Targets Classification on Multispectral Images using Connectionists Methods. Am. J. Phys. Appl. 2015, 3(3), 86-91. doi: 10.11648/j.ajpa.20150303.14

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AMA Style

Samir Zeriouh, Mustapha Boutahri, Said El Yamani, Ahmed Roukhe. Targets Classification on Multispectral Images using Connectionists Methods. Am J Phys Appl. 2015;3(3):86-91. doi: 10.11648/j.ajpa.20150303.14

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@article{10.11648/j.ajpa.20150303.14,
  author = {Samir Zeriouh and Mustapha Boutahri and Said El Yamani and Ahmed Roukhe},
  title = {Targets Classification on Multispectral Images using Connectionists Methods},
  journal = {American Journal of Physics and Applications},
  volume = {3},
  number = {3},
  pages = {86-91},
  doi = {10.11648/j.ajpa.20150303.14},
  url = {https://doi.org/10.11648/j.ajpa.20150303.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajpa.20150303.14},
  abstract = {Identification of targets on remote sensing images depends mainly on the databases representing different classes. In this context, this paper proposes a connectionist system using a two-dimensional Kohonen self-organizing map to build a database of some identified targets on a multi-band satellite image. After an enhancing process, essentially based on a non-linear filtering, the system performs a non-supervised classification of a reference image in order to extract the sequence of samples of the reflectance coefficients related to the desired targets. This classification will be used later for automatic extraction of these targets on other stages.},
 year = {2015}
}

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TY  - JOUR
T1  - Targets Classification on Multispectral Images using Connectionists Methods
AU  - Samir Zeriouh
AU  - Mustapha Boutahri
AU  - Said El Yamani
AU  - Ahmed Roukhe
Y1  - 2015/04/27
PY  - 2015
N1  - https://doi.org/10.11648/j.ajpa.20150303.14
DO  - 10.11648/j.ajpa.20150303.14
T2  - American Journal of Physics and Applications
JF  - American Journal of Physics and Applications
JO  - American Journal of Physics and Applications
SP  - 86
EP  - 91
PB  - Science Publishing Group
SN  - 2330-4308
UR  - https://doi.org/10.11648/j.ajpa.20150303.14
AB  - Identification of targets on remote sensing images depends mainly on the databases representing different classes. In this context, this paper proposes a connectionist system using a two-dimensional Kohonen self-organizing map to build a database of some identified targets on a multi-band satellite image. After an enhancing process, essentially based on a non-linear filtering, the system performs a non-supervised classification of a reference image in order to extract the sequence of samples of the reflectance coefficients related to the desired targets. This classification will be used later for automatic extraction of these targets on other stages.
VL  - 3
IS  - 3
ER  -

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Author Information

Samir Zeriouh

Information Optronic Treatment Team, Atomic, Mechanical, Photonic and Energy Laboratory, Faculty of Science, Moulay Ismail University, Zitoune, Meknès, Morocco
Mustapha Boutahri

Information Optronic Treatment Team, Atomic, Mechanical, Photonic and Energy Laboratory, Faculty of Science, Moulay Ismail University, Zitoune, Meknès, Morocco
Said El Yamani

Information Optronic Treatment Team, Atomic, Mechanical, Photonic and Energy Laboratory, Faculty of Science, Moulay Ismail University, Zitoune, Meknès, Morocco
Ahmed Roukhe

Information Optronic Treatment Team, Atomic, Mechanical, Photonic and Energy Laboratory, Faculty of Science, Moulay Ismail University, Zitoune, Meknès, Morocco

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Plain Text BibTeX RIS

APA Style

Samir Zeriouh, Mustapha Boutahri, Said El Yamani, Ahmed Roukhe. (2015). Targets Classification on Multispectral Images using Connectionists Methods. American Journal of Physics and Applications, 3(3), 86-91. https://doi.org/10.11648/j.ajpa.20150303.14

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ACS Style

Samir Zeriouh; Mustapha Boutahri; Said El Yamani; Ahmed Roukhe. Targets Classification on Multispectral Images using Connectionists Methods. Am. J. Phys. Appl. 2015, 3(3), 86-91. doi: 10.11648/j.ajpa.20150303.14

Copy | Download

AMA Style

Samir Zeriouh, Mustapha Boutahri, Said El Yamani, Ahmed Roukhe. Targets Classification on Multispectral Images using Connectionists Methods. Am J Phys Appl. 2015;3(3):86-91. doi: 10.11648/j.ajpa.20150303.14

Copy | Download

@article{10.11648/j.ajpa.20150303.14,
  author = {Samir Zeriouh and Mustapha Boutahri and Said El Yamani and Ahmed Roukhe},
  title = {Targets Classification on Multispectral Images using Connectionists Methods},
  journal = {American Journal of Physics and Applications},
  volume = {3},
  number = {3},
  pages = {86-91},
  doi = {10.11648/j.ajpa.20150303.14},
  url = {https://doi.org/10.11648/j.ajpa.20150303.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajpa.20150303.14},
  abstract = {Identification of targets on remote sensing images depends mainly on the databases representing different classes. In this context, this paper proposes a connectionist system using a two-dimensional Kohonen self-organizing map to build a database of some identified targets on a multi-band satellite image. After an enhancing process, essentially based on a non-linear filtering, the system performs a non-supervised classification of a reference image in order to extract the sequence of samples of the reflectance coefficients related to the desired targets. This classification will be used later for automatic extraction of these targets on other stages.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Targets Classification on Multispectral Images using Connectionists Methods
AU  - Samir Zeriouh
AU  - Mustapha Boutahri
AU  - Said El Yamani
AU  - Ahmed Roukhe
Y1  - 2015/04/27
PY  - 2015
N1  - https://doi.org/10.11648/j.ajpa.20150303.14
DO  - 10.11648/j.ajpa.20150303.14
T2  - American Journal of Physics and Applications
JF  - American Journal of Physics and Applications
JO  - American Journal of Physics and Applications
SP  - 86
EP  - 91
PB  - Science Publishing Group
SN  - 2330-4308
UR  - https://doi.org/10.11648/j.ajpa.20150303.14
AB  - Identification of targets on remote sensing images depends mainly on the databases representing different classes. In this context, this paper proposes a connectionist system using a two-dimensional Kohonen self-organizing map to build a database of some identified targets on a multi-band satellite image. After an enhancing process, essentially based on a non-linear filtering, the system performs a non-supervised classification of a reference image in order to extract the sequence of samples of the reflectance coefficients related to the desired targets. This classification will be used later for automatic extraction of these targets on other stages.
VL  - 3
IS  - 3
ER  -

Copy | Download