C. Chang, Hyperspectral Data Exploitation: Theory and Applications, 2007.
DOI : 10.1002/0470124628

G. Camps-valls and L. Bruzzone, Kernel-based methods for hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.6, pp.1351-1362, 2005.
DOI : 10.1109/TGRS.2005.846154

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

L. Bruzzone and L. Carlin, A Multilevel Context-Based System for Classification of Very High Spatial Resolution Images, IEEE Transactions on Geoscience and Remote Sensing, vol.44, issue.9, pp.2587-2600, 2006.
DOI : 10.1109/TGRS.2006.875360

Y. Tarabalka, J. C. Tilton, J. A. Benediktsson, and J. Chanussot, A Marker-Based Approach for the Automated Selection of a Single Segmentation From a Hierarchical Set of Image Segmentations, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.5, issue.1, pp.262-272, 2012.
DOI : 10.1109/JSTARS.2011.2173466

URL : https://hal.archives-ouvertes.fr/hal-00729001

M. D. Mura, A. Villa, J. Benediktsson, J. Chanussot, and L. Bruzzone, Classification of Hyperspectral Images by Using Extended Morphological Attribute Profiles and Independent Component Analysis, IEEE Geoscience and Remote Sensing Letters, vol.8, issue.3, pp.542-546, 2011.
DOI : 10.1109/LGRS.2010.2091253

URL : https://hal.archives-ouvertes.fr/hal-00578886

A. Farag, R. Mohamed, and A. El-baz, A unified framework for MAP estimation in remote sensing image segmentation, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.7, pp.1617-1634, 2005.
DOI : 10.1109/TGRS.2005.849059

J. Beaulieu and M. Goldberg, Hierarchy in picture segmentation: a stepwise optimization approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.2, pp.150-163, 1989.
DOI : 10.1109/34.16711

X. Huang and L. Zhang, A comparative study of spatial approaches for urban mapping using hyperspectral ROSIS images over Pavia City, northern Italy, International Journal of Remote Sensing, vol.44, issue.12, pp.3205-3221, 2009.
DOI : 10.1080/01431160802559046

S. V. Linden, A. Janz, B. Waske, M. Eiden, and P. Hostert, Classifying segmented hyperspectral data from a heterogeneous urban environment using support vector machines, Journal of Applied Remote Sensing, vol.1, issue.1, p.13543, 2007.
DOI : 10.1117/1.2813466

M. Baatz and A. Schape, Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation, Angewandte Geographische Informationsverarbeitung, 2000.

Y. Tarabalka, J. A. Benediktsson, and J. Chanussot, Classification of hyperspectral data using Support Vector Machines and adaptive neighborhoods, Proc. of the 6th EARSeL SIG IS workshop, pp.1-6, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00372301

Y. Tarabalka and J. C. Tilton, Improved hierarchical optimization-based classification of hyperspectral images using shape analysis, 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012.
DOI : 10.1109/IGARSS.2012.6351272

URL : https://hal.archives-ouvertes.fr/hal-00729038

R. L. Kettig and D. A. Landgrebe, Classification of Multispectral Image Data by Extraction and Classification of Homogeneous Objects, IEEE Transactions on Geoscience Electronics, vol.14, issue.1
DOI : 10.1109/TGE.1976.294460