Title :
Object recognition in urban hyperspectral images using Binary Partition Tree representation
Author :
Valero, S. ; Salembier, Philippe ; Chanussot, Jocelyn
Author_Institution :
CNES, Univ. de Toulouse, Toulouse, France
Abstract :
In this work, an image representation based on Binary Partition Tree is proposed for object detection in hyperspectral images. 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. Experimental results demonstrate the good performances of this BPT-based approach.
Keywords :
geophysical image processing; hyperspectral imaging; image representation; object recognition; remote sensing; tree data structures; BPT representation; BPT-based approach; binary partition tree representation; image representation; object detection; object recognition; region-based perspective; remote sensing; robust object identification scheme; search space; spatial information; spectral information; urban hyperspectral images; Feature extraction; Hyperspectral imaging; Image segmentation; Merging; Object detection; Support vector machines; BPT; Object detection; Region-based image analysis; hyperspectral;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6723734
