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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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2018-06, Vol.56 (6), p.3611-3623
Main Authors: Mendez Dominguez, Elias, Meier, Erich, Small, David, Schaepman, Michael E., Bruzzone, Lorenzo, Henke, Daniel
Format: Article
Language:English
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
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Summary: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.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2018.2805471