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- W2611687527 abstract "We propose a decision-level architecture that combines synthetic aperture radar (SAR) and an infrared (IR)sensor for automatic target detection. We present a new size-based feature, called target-silhouette to reduce thenumber of false alarms produced by the conventional target-detection algorithm. Boolean Map Visual Theoryis used to combine a pair of SAR and IR images to generate the target-enhanced map. Then basic beliefassignment is used to transform this map into a belief map. The detection results of sensors are combined tobuild the target-silhouette map. We integrate the fusion mass and the target-silhouette map on the decisionlevel to exclude false alarms. The proposed algorithm is evaluated using a SAR and IR synthetic databasegenerated by SE-WORKBENCH simulator, and compared with conventional algorithms. The proposed fusionscheme achieves higher detection rate and lower false alarm rate than the conventional algorithms." @default.
- W2611687527 created "2017-05-12" @default.
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- W2611687527 date "2017-05-02" @default.
- W2611687527 modified "2023-09-22" @default.
- W2611687527 title "Decision-level fusion of SAR and IR sensor information for automatic target detection" @default.
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- W2611687527 doi "https://doi.org/10.1117/12.2262271" @default.
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