Object recognition in hyperspectral images using Binary Partition Tree representation
Visualitza/Obre
10.1016/j.patrec.2015.01.003
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/27385
Tipus de documentArticle
Data publicació2015-04-15
Condicions d'accésAccés obert
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Abstract
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.
CitacióValero, S.; Salembier, P.; Chanussot, J. Object recognition in hyperspectral images using Binary Partition Tree representation. "Pattern recognition letters", 15 Abril 2015, vol. 56, p. 45-51.
ISSN0167-8655
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Valero_PRLetters.pdf | 1,816Mb | Visualitza/Obre |