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Title:
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Hyperspectral image segmentation using binary partition trees
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Author:
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Valero, 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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The work presented here proposes a new Binary Partition Tree pruning strategy aimed at the segmentation of hyperspectral images. The BPT is a region-based representation of images that involves a reduced number of elementary primitives and therefore allows to design a robust and efficient segmentation algorithm. Here, the regions contained in the BPT branches are studied by recursive spectral graph partitioning. The goal is to remove subtrees composed of nodes which are considered to be similar. To this end, affinity matrices on the tree branches are computed using a new distance-based measure depending on canonical correlations relating principal coordinates. Experimental results have demonstrated the good performances of BPT construction and pruning. |
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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::Processament de la imatge i del senyal vídeo
-Image processing --Digital techniques.
-Spectroscopic imaging
-Imatges -- Processament -- Tècniques digitals
-Reconeixement de formes (Informàtica) |
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Rights:
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Document type:
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Article - Published version
Conference Object |
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Published by:
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IEEE
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Share:
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