A Multisquint Framework for Change Detection in High-Resolution Multitemporal SAR Images
Change detection from multitemporal synthetic aperture radar (SAR) images enables mapping applications for earth environmental observation, human activity monitoring, and urban studies. We expand the use of SAR data beyond single-look processing to include the spatial response of targets. This infor...
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| Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2018-06, Vol.56 (6), p.3611-3623 |
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| container_title | IEEE transactions on geoscience and remote sensing |
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| creator | Mendez Dominguez, Elias Meier, Erich Small, David Schaepman, Michael E. Bruzzone, Lorenzo Henke, Daniel |
| description | Change detection from multitemporal synthetic aperture radar (SAR) images enables mapping applications for earth environmental observation, human activity monitoring, and urban studies. We expand the use of SAR data beyond single-look processing to include the spatial response of targets. This information is derived from a multisquint framework similar to beamforming. To preserve changes detected at nominal resolution, a three-stage change detector exploiting single-look and multisquint processing mode is proposed to mitigate false alarms caused by image artifacts typically found in high-resolution SAR imagery and urban scenarios. After applying the proposed method to multitemporal images, the false alarm rate was reduced by a factor 3, while preserving 95% of the detection rate offered by traditional schemes. |
| doi_str_mv | 10.1109/TGRS.2018.2805471 |
| format | Article |
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(IEEE) 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-da9f41746148147bab174589a42482fc56542984a1c29a780dbdacb444463c563</citedby><cites>FETCH-LOGICAL-c293t-da9f41746148147bab174589a42482fc56542984a1c29a780dbdacb444463c563</cites><orcidid>0000-0002-9627-9565 ; 0000-0002-1461-9424 ; 0000-0002-6036-459X ; 0000-0002-9649-0205</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8305538$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8305538$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Mendez Dominguez, Elias</creatorcontrib><creatorcontrib>Meier, Erich</creatorcontrib><creatorcontrib>Small, David</creatorcontrib><creatorcontrib>Schaepman, Michael E.</creatorcontrib><creatorcontrib>Bruzzone, Lorenzo</creatorcontrib><creatorcontrib>Henke, Daniel</creatorcontrib><title>A Multisquint Framework for Change Detection in High-Resolution Multitemporal SAR Images</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>Change detection from multitemporal synthetic aperture radar (SAR) images enables mapping applications for earth environmental observation, human activity monitoring, and urban studies. 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| subjects | Array signal processing Azimuth Backscatter Beamforming Change detection Data processing Detection Detectors Earth Environmental monitoring False alarms Frameworks High resolution Image detection Image processing Image resolution Imagery Information processing Mapping Radar imaging remote sensing Resolution SAR (radar) spatial filters Spatial resolution Synthetic aperture radar synthetic aperture radar (SAR) urban areas Urban studies wavelets |
| title | A Multisquint Framework for Change Detection in High-Resolution Multitemporal SAR Images |
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