Loading…

SAR image segmentation with active contours and level sets

Automatic interpretation of synthetic aperture radar (SAR) images requires automatic segmentation of these images. Image segmentation is a fundamental problem in computer vision, particularly difficult with SAR images because of the presence of strong, multiplicative speckle noise. The purpose of th...

Full description

Saved in:

Bibliographic Details
Main Authors:	Ayed, I.B., Vazquez, C., Mitiche, A., Belhadj, Z.
Format:	Conference Proceeding
Language:	English
Subjects:	Active contours Applied sciences Artificial intelligence Computer science control theory systems Computer vision Equations Exact sciences and technology Histograms Image segmentation Level set Pattern recognition. Digital image processing. Computational geometry Robustness Speckle Synthetic aperture radar Topology
Online Access:	Request full text
Tags:	Add Tag No Tags, Be the first to tag this record!

cited_by
cites
container_end_page	2720 Vol. 4
container_issue
container_start_page	2717
container_title
container_volume	4
creator	Ayed, I.B. Vazquez, C. Mitiche, A. Belhadj, Z.
description	Automatic interpretation of synthetic aperture radar (SAR) images requires automatic segmentation of these images. Image segmentation is a fundamental problem in computer vision, particularly difficult with SAR images because of the presence of strong, multiplicative speckle noise. The purpose of this study is to investigate a novel algorithm for segmenting a synthetic aperture radar (SAR) image into a fixed but arbitrary number of Gamma-homogeneous regions. This unsupervised algorithm is based on active contours and consists in evolving closed simple planar curves to minimize a criterion containing a term of conformity of data to a model of SAR image intensity and a term of regularization. The curve evolution equations are implemented via level sets for numerical stability and to allow variations in the topology of the curves during their evolution. Examples are given using real SAR images.
doi_str_mv	10.1109/ICIP.2004.1421665
format	conference_proceeding
fullrecord	<record><control><sourceid>pascalfrancis_6IE</sourceid><recordid>TN_cdi_pascalfrancis_primary_17612028</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1421665</ieee_id><sourcerecordid>17612028</sourcerecordid><originalsourceid>FETCH-LOGICAL-i205t-d021e1ba277481521312b20aef3b673f3d65bdc2ccece9164f68b486701d153</originalsourceid><addsrcrecordid>eNpFkEtLw0AUhQcfYFv9AeJmNi5T773zyNRdKT4CBcW6L5PJTY2kacmMFf-9gQquzuJ8nHM4QlwjTBFhdlcsitcpAegpakJrzYkYkXKYOaNnp2IMuQPljNHqTIzQEGXaObgQ4xg_AQhQ4Ujcr-Zvstn6DcvImy13yadm18nvJn1IH1JzYBl2Xdp99VH6rpItH7gd2BQvxXnt28hXfzoRq8eH98Vztnx5KhbzZdYQmJRVQMhYespz7YYZQy2VBJ5rVdpc1aqypqwChcCBZ2h1bV2pnc0BKzRqIm6PqXsfg2_r3nehiet9P4zuf9aYWyQgN3A3R65h5n_7-Iz6BZ8cVAc</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>SAR image segmentation with active contours and level sets</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Ayed, I.B. ; Vazquez, C. ; Mitiche, A. ; Belhadj, Z.</creator><creatorcontrib>Ayed, I.B. ; Vazquez, C. ; Mitiche, A. ; Belhadj, Z.</creatorcontrib><description>Automatic interpretation of synthetic aperture radar (SAR) images requires automatic segmentation of these images. Image segmentation is a fundamental problem in computer vision, particularly difficult with SAR images because of the presence of strong, multiplicative speckle noise. The purpose of this study is to investigate a novel algorithm for segmenting a synthetic aperture radar (SAR) image into a fixed but arbitrary number of Gamma-homogeneous regions. This unsupervised algorithm is based on active contours and consists in evolving closed simple planar curves to minimize a criterion containing a term of conformity of data to a model of SAR image intensity and a term of regularization. The curve evolution equations are implemented via level sets for numerical stability and to allow variations in the topology of the curves during their evolution. Examples are given using real SAR images.</description><identifier>ISSN: 1522-4880</identifier><identifier>ISBN: 0780385543</identifier><identifier>ISBN: 9780780385542</identifier><identifier>EISSN: 2381-8549</identifier><identifier>DOI: 10.1109/ICIP.2004.1421665</identifier><language>eng</language><publisher>Piscataway NJ: IEEE</publisher><subject>Active contours ; Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Computer vision ; Equations ; Exact sciences and technology ; Histograms ; Image segmentation ; Level set ; Pattern recognition. Digital image processing. Computational geometry ; Robustness ; Speckle ; Synthetic aperture radar ; Topology</subject><ispartof>2004 International Conference on Image Processing, 2004. ICIP '04, 2004, Vol.4, p.2717-2720 Vol. 4</ispartof><rights>2006 INIST-CNRS</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1421665$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1421665$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17612028$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Ayed, I.B.</creatorcontrib><creatorcontrib>Vazquez, C.</creatorcontrib><creatorcontrib>Mitiche, A.</creatorcontrib><creatorcontrib>Belhadj, Z.</creatorcontrib><title>SAR image segmentation with active contours and level sets</title><title>2004 International Conference on Image Processing, 2004. ICIP '04</title><addtitle>ICIP</addtitle><description>Automatic interpretation of synthetic aperture radar (SAR) images requires automatic segmentation of these images. Image segmentation is a fundamental problem in computer vision, particularly difficult with SAR images because of the presence of strong, multiplicative speckle noise. The purpose of this study is to investigate a novel algorithm for segmenting a synthetic aperture radar (SAR) image into a fixed but arbitrary number of Gamma-homogeneous regions. This unsupervised algorithm is based on active contours and consists in evolving closed simple planar curves to minimize a criterion containing a term of conformity of data to a model of SAR image intensity and a term of regularization. The curve evolution equations are implemented via level sets for numerical stability and to allow variations in the topology of the curves during their evolution. Examples are given using real SAR images.</description><subject>Active contours</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Computer vision</subject><subject>Equations</subject><subject>Exact sciences and technology</subject><subject>Histograms</subject><subject>Image segmentation</subject><subject>Level set</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Robustness</subject><subject>Speckle</subject><subject>Synthetic aperture radar</subject><subject>Topology</subject><issn>1522-4880</issn><issn>2381-8549</issn><isbn>0780385543</isbn><isbn>9780780385542</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpFkEtLw0AUhQcfYFv9AeJmNi5T773zyNRdKT4CBcW6L5PJTY2kacmMFf-9gQquzuJ8nHM4QlwjTBFhdlcsitcpAegpakJrzYkYkXKYOaNnp2IMuQPljNHqTIzQEGXaObgQ4xg_AQhQ4Ujcr-Zvstn6DcvImy13yadm18nvJn1IH1JzYBl2Xdp99VH6rpItH7gd2BQvxXnt28hXfzoRq8eH98Vztnx5KhbzZdYQmJRVQMhYespz7YYZQy2VBJ5rVdpc1aqypqwChcCBZ2h1bV2pnc0BKzRqIm6PqXsfg2_r3nehiet9P4zuf9aYWyQgN3A3R65h5n_7-Iz6BZ8cVAc</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Ayed, I.B.</creator><creator>Vazquez, C.</creator><creator>Mitiche, A.</creator><creator>Belhadj, Z.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>SAR image segmentation with active contours and level sets</title><author>Ayed, I.B. ; Vazquez, C. ; Mitiche, A. ; Belhadj, Z.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i205t-d021e1ba277481521312b20aef3b673f3d65bdc2ccece9164f68b486701d153</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Active contours</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Computer vision</topic><topic>Equations</topic><topic>Exact sciences and technology</topic><topic>Histograms</topic><topic>Image segmentation</topic><topic>Level set</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Robustness</topic><topic>Speckle</topic><topic>Synthetic aperture radar</topic><topic>Topology</topic><toplevel>online_resources</toplevel><creatorcontrib>Ayed, I.B.</creatorcontrib><creatorcontrib>Vazquez, C.</creatorcontrib><creatorcontrib>Mitiche, A.</creatorcontrib><creatorcontrib>Belhadj, Z.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library Online</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ayed, I.B.</au><au>Vazquez, C.</au><au>Mitiche, A.</au><au>Belhadj, Z.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>SAR image segmentation with active contours and level sets</atitle><btitle>2004 International Conference on Image Processing, 2004. ICIP '04</btitle><stitle>ICIP</stitle><date>2004</date><risdate>2004</risdate><volume>4</volume><spage>2717</spage><epage>2720 Vol. 4</epage><pages>2717-2720 Vol. 4</pages><issn>1522-4880</issn><eissn>2381-8549</eissn><isbn>0780385543</isbn><isbn>9780780385542</isbn><abstract>Automatic interpretation of synthetic aperture radar (SAR) images requires automatic segmentation of these images. Image segmentation is a fundamental problem in computer vision, particularly difficult with SAR images because of the presence of strong, multiplicative speckle noise. The purpose of this study is to investigate a novel algorithm for segmenting a synthetic aperture radar (SAR) image into a fixed but arbitrary number of Gamma-homogeneous regions. This unsupervised algorithm is based on active contours and consists in evolving closed simple planar curves to minimize a criterion containing a term of conformity of data to a model of SAR image intensity and a term of regularization. The curve evolution equations are implemented via level sets for numerical stability and to allow variations in the topology of the curves during their evolution. Examples are given using real SAR images.</abstract><cop>Piscataway NJ</cop><pub>IEEE</pub><doi>10.1109/ICIP.2004.1421665</doi></addata></record>
fulltext	fulltext_linktorsrc
identifier	ISSN: 1522-4880
ispartof	2004 International Conference on Image Processing, 2004. ICIP '04, 2004, Vol.4, p.2717-2720 Vol. 4
issn	1522-4880 2381-8549
language	eng
recordid	cdi_pascalfrancis_primary_17612028
source	IEEE Electronic Library (IEL) Conference Proceedings
subjects	Active contours Applied sciences Artificial intelligence Computer science control theory systems Computer vision Equations Exact sciences and technology Histograms Image segmentation Level set Pattern recognition. Digital image processing. Computational geometry Robustness Speckle Synthetic aperture radar Topology
title	SAR image segmentation with active contours and level sets
url	http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T09%3A32%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-pascalfrancis_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=SAR%20image%20segmentation%20with%20active%20contours%20and%20level%20sets&rft.btitle=2004%20International%20Conference%20on%20Image%20Processing,%202004.%20ICIP%20'04&rft.au=Ayed,%20I.B.&rft.date=2004&rft.volume=4&rft.spage=2717&rft.epage=2720%20Vol.%204&rft.pages=2717-2720%20Vol.%204&rft.issn=1522-4880&rft.eissn=2381-8549&rft.isbn=0780385543&rft.isbn_list=9780780385542&rft_id=info:doi/10.1109/ICIP.2004.1421665&rft_dat=%3Cpascalfrancis_6IE%3E17612028%3C/pascalfrancis_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i205t-d021e1ba277481521312b20aef3b673f3d65bdc2ccece9164f68b486701d153%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=1421665&rfr_iscdi=true