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Object recognitions in radarsat-1 sar data using fuzzy classification

This study is aimed to utilize fuzzy classification for different object detections that is urban, infrastructure and coastal water in RADARSAT-1 SAR S2 mode data. Prior to fuzzy classification, Lee algorithm with kernel window sizes of 7 × 7 pixels and lines is implemented to S2 mode data. Indeed,...

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主要な著者: Marghany, Maged Mahmoud, Hashim, Mazlan, Moradi, Farideh
フォーマット: 論文
出版事項: Academic Journals Inc. 2011
主題:
G Geography. Anthropology. Recreation
オンライン･アクセス:http://eprints.utm.my/id/eprint/29665/
https://academicjournals.org/journal/IJPS/article-abstract/C527C0E24820
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spelling my.utm.296652019-04-25T01:18:21Z http://eprints.utm.my/id/eprint/29665/ Object recognitions in radarsat-1 sar data using fuzzy classification Marghany, Maged Mahmoud Hashim, Mazlan Moradi, Farideh G Geography. Anthropology. Recreation This study is aimed to utilize fuzzy classification for different object detections that is urban, infrastructure and coastal water in RADARSAT-1 SAR S2 mode data. Prior to fuzzy classification, Lee algorithm with kernel window sizes of 7 × 7 pixels and lines is implemented to S2 mode data. Indeed, speckle reduction is performed using Lee algorithm. The results show that Lee algorithm is able to provide excellent information about linear infrastructure and urban features in SAR data. Further, fuzzy classification can discriminate between urban zone and coastal waters. In conclusion, the integration between Lee algorithm and fuzzy classification can be used for different object recognitions in S2 mode data. Academic Journals Inc. 2011-08-18 Article PeerReviewed Marghany, Maged Mahmoud and Hashim, Mazlan and Moradi, Farideh (2011) Object recognitions in radarsat-1 sar data using fuzzy classification. International Journal of Physical Sciences, 6 (16). pp. 4038-4043. ISSN 1992-1950 https://academicjournals.org/journal/IJPS/article-abstract/C527C0E24820
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic G Geography. Anthropology. Recreation
spellingShingle G Geography. Anthropology. Recreation
Marghany, Maged Mahmoud
Hashim, Mazlan
Moradi, Farideh
Object recognitions in radarsat-1 sar data using fuzzy classification
description This study is aimed to utilize fuzzy classification for different object detections that is urban, infrastructure and coastal water in RADARSAT-1 SAR S2 mode data. Prior to fuzzy classification, Lee algorithm with kernel window sizes of 7 × 7 pixels and lines is implemented to S2 mode data. Indeed, speckle reduction is performed using Lee algorithm. The results show that Lee algorithm is able to provide excellent information about linear infrastructure and urban features in SAR data. Further, fuzzy classification can discriminate between urban zone and coastal waters. In conclusion, the integration between Lee algorithm and fuzzy classification can be used for different object recognitions in S2 mode data.
format Article
author Marghany, Maged Mahmoud
Hashim, Mazlan
Moradi, Farideh
author_facet Marghany, Maged Mahmoud
Hashim, Mazlan
Moradi, Farideh
author_sort Marghany, Maged Mahmoud
title Object recognitions in radarsat-1 sar data using fuzzy classification
title_short Object recognitions in radarsat-1 sar data using fuzzy classification
title_full Object recognitions in radarsat-1 sar data using fuzzy classification
title_fullStr Object recognitions in radarsat-1 sar data using fuzzy classification
title_full_unstemmed Object recognitions in radarsat-1 sar data using fuzzy classification
title_sort object recognitions in radarsat-1 sar data using fuzzy classification
publisher Academic Journals Inc.
publishDate 2011
url http://eprints.utm.my/id/eprint/29665/
https://academicjournals.org/journal/IJPS/article-abstract/C527C0E24820
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score 13.153044

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