Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm

Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm

Remote sensing applications such as Ecological monitoring, Disaster monitoring, Volcanic monitoring, surveillance and reconnaissance requires broad range imaginary data with very high resolution. Data captured under different times such as day or night and under different weather conditions poses ad...

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Bibliographic Details
Main Author: Rashid Hussain
Format: Article
Language:English
Published: International Academy of Ecology and Environmental Sciences 2012-12-01
Series:Computational Ecology and Software
Subjects:
Synthetic Aperture Radar (SAR)
Fuzzy c-means (FCM) clustering algorithm
satellite radar image
remote sensing
ecological monitoring
Online Access:http://www.iaees.org/publications/journals/ces/articles/2012-2(4)/synthetic-aperture-radar-images-features-clustering.pdf
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spelling doaj-b0eb5c2cde0f45b7b7c2515518df11a92020-11-24T22:36:51ZengInternational Academy of Ecology and Environmental SciencesComputational Ecology and Software2220-721X2012-12-0124220225Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithmRashid HussainRemote sensing applications such as Ecological monitoring, Disaster monitoring, Volcanic monitoring, surveillance and reconnaissance requires broad range imaginary data with very high resolution. Data captured under different times such as day or night and under different weather conditions poses adverse affects on retrieved results. Synthetic Aperture Radar (SAR) technology is used to mitigate such adverse effects. Recently SAR technology re-emerges because of the decrease in the cost of electronic components and tremendous advancement in computing power. This paper provides an application of Fuzzy c-means (FCM) clustering algorithm to SAR Images. The objective of this study is to segment various region of interest in remote sensing images for ecological monitoring.http://www.iaees.org/publications/journals/ces/articles/2012-2(4)/synthetic-aperture-radar-images-features-clustering.pdfSynthetic Aperture Radar (SAR)Fuzzy c-means (FCM) clustering algorithmsatellite radar imageremote sensingecological monitoring
collection DOAJ
language English
format Article
sources DOAJ
author Rashid Hussain
spellingShingle Rashid Hussain
Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm
Computational Ecology and Software
Synthetic Aperture Radar (SAR)
Fuzzy c-means (FCM) clustering algorithm
satellite radar image
remote sensing
ecological monitoring
author_facet Rashid Hussain
author_sort Rashid Hussain
title Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm
title_short Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm
title_full Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm
title_fullStr Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm
title_full_unstemmed Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm
title_sort synthetic aperture radar (sar) images features clustering using fuzzy c-means (fcm) clustering algorithm
publisher International Academy of Ecology and Environmental Sciences
series Computational Ecology and Software
issn 2220-721X
publishDate 2012-12-01
description Remote sensing applications such as Ecological monitoring, Disaster monitoring, Volcanic monitoring, surveillance and reconnaissance requires broad range imaginary data with very high resolution. Data captured under different times such as day or night and under different weather conditions poses adverse affects on retrieved results. Synthetic Aperture Radar (SAR) technology is used to mitigate such adverse effects. Recently SAR technology re-emerges because of the decrease in the cost of electronic components and tremendous advancement in computing power. This paper provides an application of Fuzzy c-means (FCM) clustering algorithm to SAR Images. The objective of this study is to segment various region of interest in remote sensing images for ecological monitoring.
topic Synthetic Aperture Radar (SAR)
Fuzzy c-means (FCM) clustering algorithm
satellite radar image
remote sensing
ecological monitoring
url http://www.iaees.org/publications/journals/ces/articles/2012-2(4)/synthetic-aperture-radar-images-features-clustering.pdf
work_keys_str_mv AT rashidhussain syntheticapertureradarsarimagesfeaturesclusteringusingfuzzycmeansfcmclusteringalgorithm
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