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Title:
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Object recognition in hyperspectral images using Binary Partition Tree representation
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Author:
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Valero Valbuena, Silvia; Salembier Clairon, Philippe Jean; Chanussot, Jocelyn
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
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Abstract:
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In this work, an image representation based on Binary Partition Tree is proposed for object detection in hyperspectral images. This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure, which succeeds in presenting: (i) the decomposition of the image in terms of coherent regions and (ii) the inclusion relations of the regions in the scene. Hence, the BPT representation defines a search space for constructing a robust object identification scheme. Spatial and spectral information are integrated in order to analyze hyperspectral images with a region based perspective. For each region represented in the BPT, spatial and spectral descriptors are computed and the likelihood that they correspond to an instantiation of the object of interest is evaluated. Experimental results demonstrate the good performances of this BPT-based approach. (C) 2015 Elsevier B.V. All rights reserved. |
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Abstract:
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Peer Reviewed |
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Subject(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes
-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció
-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
-Remote sensing
-Image processing
-Pattern recognition systems
-Object based image analysis
-Binary Partition Tree
-Hyperspectral images
-Object recognition
-Remote-Sensing images
-Mathematical morphology
-Information
-Teledetecció
-Imatges -- Processament
-Reconeixement de formes (Informàtica) |
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Rights:
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Document type:
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Article - Submitted version
Article |
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