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Título:
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Stereoscopic road network extraction by decision-level fusion of optical and SAR imagery
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Autor/a:
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He, Chu; Yang, Fang; Yin, Sha; Deng, Xinping; Liao, Mingsheng
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
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Abstract:
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A new stereoscopic road network extraction framework based on the decision-level fusion of optical and Synthetic Aperture Radar (SAR) imagery is proposed in this paper. Three steps are included in this framework: 1) road segment extraction and structure optimization through SAR imagery, 2) road segment extraction and stereoscopic information collection through optical imagery, and 3) fusion of the SAR result with the optical image and the stereoscopic information. In this study, our new road network grouping algorithm called road network grouping based on the multi-scale geometric analysis of detector Response is used, with the improved footprint method, and the stereoscopic inversion algorithm. The most important finding of our work lies in the fusion step, by which a stereoscopic road network can be acquired after going through the three aforementioned processes and by fusing the stereoscopic information obtained from optical imagery and road network extracted from SAR imagery. Our algorithm is tested on the real TerraSAR-X and QuickBird data. |
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Abstract:
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Peer Reviewed |
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Materia(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radar
-Àrees temàtiques de la UPC::Enginyeria civil::Infraestructures i modelització dels transports
-Synthetic aperture radar
-Roads
-Decision-level fusion
-Optical
-Road network extraction
-Stereoscopic information
-Synthetic aperture radar
-Radar d'obertura sintètica
-Carreteres |
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Derechos:
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Tipo de documento:
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Artículo - Versión publicada
Artículo |
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Compartir:
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