Automatic water canal detection in multispectral satellite images
In this paper, a method for automatically detecting water regions and classifying water canals containing water in high resolution multispectral satellite images in a rule based manner is proposed. As water canals may be of different lengths and widths, indices employed in the literature and image g...
Gespeichert in:
Hauptverfasser: | , , , , , , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng ; tur |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 4 |
---|---|
container_issue | |
container_start_page | 1 |
container_title | |
container_volume | |
creator | Gedik, E. Cinar, U. Karaman, E. Yardimci, Y. Halici, U. Pakin, K. Ergezer, H. |
description | In this paper, a method for automatically detecting water regions and classifying water canals containing water in high resolution multispectral satellite images in a rule based manner is proposed. As water canals may be of different lengths and widths, indices employed in the literature and image gradients are used adaptively to classify water regions. The well known spatial properties of water canals are used to determine the water canals among the extracted water regions. The proposed algorithm is tested on high resolution multispectral satellite images covering large areas and satisfactory results are obtained. |
doi_str_mv | 10.1109/SIU.2013.6531535 |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6531535</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6531535</ieee_id><sourcerecordid>6531535</sourcerecordid><originalsourceid>FETCH-LOGICAL-i105t-797c549b260927c75a085f6ec309e65dec412c1c05330a0ef99a883818dfce063</originalsourceid><addsrcrecordid>eNpVT01Lw0AQXRFBqbkLXvYPJM5mMvtxDMWPQsGD9lzWzURWkrRkt4j_3oC9eHq8j5nHE-JOQaUUuIe3za6qQWGlCRUhXYjCGasabZBIo778x2t3LYqUvgBgudbO6hvRtqd8GH2OQX77zLMMfvKD7DhzyPEwyTjJ8TTkmI6LMC9WWmLDEDPLOPpPTrfiqvdD4uKMK7F7enxfv5Tb1-fNut2WUQHl0jgTqHEftQZXm2DIg6Vec0BwrKnj0Kg6qACECB64d85bi1bZrg8MGlfi_u9vZOb9cV7a55_9eTj-AsnNS0Y</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Automatic water canal detection in multispectral satellite images</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Gedik, E. ; Cinar, U. ; Karaman, E. ; Yardimci, Y. ; Halici, U. ; Pakin, K. ; Ergezer, H.</creator><creatorcontrib>Gedik, E. ; Cinar, U. ; Karaman, E. ; Yardimci, Y. ; Halici, U. ; Pakin, K. ; Ergezer, H.</creatorcontrib><description>In this paper, a method for automatically detecting water regions and classifying water canals containing water in high resolution multispectral satellite images in a rule based manner is proposed. As water canals may be of different lengths and widths, indices employed in the literature and image gradients are used adaptively to classify water regions. The well known spatial properties of water canals are used to determine the water canals among the extracted water regions. The proposed algorithm is tested on high resolution multispectral satellite images covering large areas and satisfactory results are obtained.</description><identifier>ISBN: 9781467355629</identifier><identifier>ISBN: 1467355623</identifier><identifier>EISBN: 9781467355636</identifier><identifier>EISBN: 1467355631</identifier><identifier>EISBN: 1467355615</identifier><identifier>EISBN: 9781467355612</identifier><identifier>DOI: 10.1109/SIU.2013.6531535</identifier><language>eng ; tur</language><publisher>IEEE</publisher><subject>Bridges ; high resolution satellite images ; Irrigation ; Remote sensing ; Satellites ; Spatial resolution ; spectral index ; structural analysis ; Water ; water canal extraction</subject><ispartof>2013 21st Signal Processing and Communications Applications Conference (SIU), 2013, p.1-4</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6531535$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6531535$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Gedik, E.</creatorcontrib><creatorcontrib>Cinar, U.</creatorcontrib><creatorcontrib>Karaman, E.</creatorcontrib><creatorcontrib>Yardimci, Y.</creatorcontrib><creatorcontrib>Halici, U.</creatorcontrib><creatorcontrib>Pakin, K.</creatorcontrib><creatorcontrib>Ergezer, H.</creatorcontrib><title>Automatic water canal detection in multispectral satellite images</title><title>2013 21st Signal Processing and Communications Applications Conference (SIU)</title><addtitle>SIU</addtitle><description>In this paper, a method for automatically detecting water regions and classifying water canals containing water in high resolution multispectral satellite images in a rule based manner is proposed. As water canals may be of different lengths and widths, indices employed in the literature and image gradients are used adaptively to classify water regions. The well known spatial properties of water canals are used to determine the water canals among the extracted water regions. The proposed algorithm is tested on high resolution multispectral satellite images covering large areas and satisfactory results are obtained.</description><subject>Bridges</subject><subject>high resolution satellite images</subject><subject>Irrigation</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>Spatial resolution</subject><subject>spectral index</subject><subject>structural analysis</subject><subject>Water</subject><subject>water canal extraction</subject><isbn>9781467355629</isbn><isbn>1467355623</isbn><isbn>9781467355636</isbn><isbn>1467355631</isbn><isbn>1467355615</isbn><isbn>9781467355612</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVT01Lw0AQXRFBqbkLXvYPJM5mMvtxDMWPQsGD9lzWzURWkrRkt4j_3oC9eHq8j5nHE-JOQaUUuIe3za6qQWGlCRUhXYjCGasabZBIo778x2t3LYqUvgBgudbO6hvRtqd8GH2OQX77zLMMfvKD7DhzyPEwyTjJ8TTkmI6LMC9WWmLDEDPLOPpPTrfiqvdD4uKMK7F7enxfv5Tb1-fNut2WUQHl0jgTqHEftQZXm2DIg6Vec0BwrKnj0Kg6qACECB64d85bi1bZrg8MGlfi_u9vZOb9cV7a55_9eTj-AsnNS0Y</recordid><startdate>201304</startdate><enddate>201304</enddate><creator>Gedik, E.</creator><creator>Cinar, U.</creator><creator>Karaman, E.</creator><creator>Yardimci, Y.</creator><creator>Halici, U.</creator><creator>Pakin, K.</creator><creator>Ergezer, H.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201304</creationdate><title>Automatic water canal detection in multispectral satellite images</title><author>Gedik, E. ; Cinar, U. ; Karaman, E. ; Yardimci, Y. ; Halici, U. ; Pakin, K. ; Ergezer, H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i105t-797c549b260927c75a085f6ec309e65dec412c1c05330a0ef99a883818dfce063</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng ; tur</language><creationdate>2013</creationdate><topic>Bridges</topic><topic>high resolution satellite images</topic><topic>Irrigation</topic><topic>Remote sensing</topic><topic>Satellites</topic><topic>Spatial resolution</topic><topic>spectral index</topic><topic>structural analysis</topic><topic>Water</topic><topic>water canal extraction</topic><toplevel>online_resources</toplevel><creatorcontrib>Gedik, E.</creatorcontrib><creatorcontrib>Cinar, U.</creatorcontrib><creatorcontrib>Karaman, E.</creatorcontrib><creatorcontrib>Yardimci, Y.</creatorcontrib><creatorcontrib>Halici, U.</creatorcontrib><creatorcontrib>Pakin, K.</creatorcontrib><creatorcontrib>Ergezer, H.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gedik, E.</au><au>Cinar, U.</au><au>Karaman, E.</au><au>Yardimci, Y.</au><au>Halici, U.</au><au>Pakin, K.</au><au>Ergezer, H.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Automatic water canal detection in multispectral satellite images</atitle><btitle>2013 21st Signal Processing and Communications Applications Conference (SIU)</btitle><stitle>SIU</stitle><date>2013-04</date><risdate>2013</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><isbn>9781467355629</isbn><isbn>1467355623</isbn><eisbn>9781467355636</eisbn><eisbn>1467355631</eisbn><eisbn>1467355615</eisbn><eisbn>9781467355612</eisbn><abstract>In this paper, a method for automatically detecting water regions and classifying water canals containing water in high resolution multispectral satellite images in a rule based manner is proposed. As water canals may be of different lengths and widths, indices employed in the literature and image gradients are used adaptively to classify water regions. The well known spatial properties of water canals are used to determine the water canals among the extracted water regions. The proposed algorithm is tested on high resolution multispectral satellite images covering large areas and satisfactory results are obtained.</abstract><pub>IEEE</pub><doi>10.1109/SIU.2013.6531535</doi><tpages>4</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISBN: 9781467355629 |
ispartof | 2013 21st Signal Processing and Communications Applications Conference (SIU), 2013, p.1-4 |
issn | |
language | eng ; tur |
recordid | cdi_ieee_primary_6531535 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Bridges high resolution satellite images Irrigation Remote sensing Satellites Spatial resolution spectral index structural analysis Water water canal extraction |
title | Automatic water canal detection in multispectral satellite images |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T15%3A54%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Automatic%20water%20canal%20detection%20in%20multispectral%20satellite%20images&rft.btitle=2013%2021st%20Signal%20Processing%20and%20Communications%20Applications%20Conference%20(SIU)&rft.au=Gedik,%20E.&rft.date=2013-04&rft.spage=1&rft.epage=4&rft.pages=1-4&rft.isbn=9781467355629&rft.isbn_list=1467355623&rft_id=info:doi/10.1109/SIU.2013.6531535&rft_dat=%3Cieee_6IE%3E6531535%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781467355636&rft.eisbn_list=1467355631&rft.eisbn_list=1467355615&rft.eisbn_list=9781467355612&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6531535&rfr_iscdi=true |