]. D. Donoghue, Remote sensing: sensors and applications, Progress in Physical Geography, vol.66, issue.3, pp.407-414, 2000.
DOI : 10.1016/S0169-555X(99)00008-2

M. Baatz, C. Hoffmann, and G. Willhauck, Progressing from object-based to object-oriented image analysis Object-Based Image Analysis, Lecture Notes in Geoinformation and Cartography, pp.29-42, 2008.

T. Blaschke, Object based image analysis for remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing, vol.65, issue.1, pp.2-16, 2010.
DOI : 10.1016/j.isprsjprs.2009.06.004

A. Puissant and C. Weber, The Utility of Very High Spatial Resolution Images to Identify Urban Objects, Geocarto International, vol.63, issue.1, pp.33-44, 2002.
DOI : 10.1080/01431168208948387
URL : https://hal.archives-ouvertes.fr/halshs-00523199

G. Forestier, C. Wemmert, and P. Gançarski, Multisource Images Analysis Using Collaborative Clustering, EURASIP Journal on Advances in Signal Processing, vol.35, issue.7, pp.1-11, 2008.
DOI : 10.1155/ASP/2006/96306
URL : https://doi.org/10.1155/2008/374095

R. Gaetano, G. Scarpa, and G. Poggi, Hierarchical Texture-Based Segmentation of Multiresolution Remote-Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.7, pp.2129-2141, 2009.
DOI : 10.1109/TGRS.2008.2010708

H. G. Akcay and S. Aksoy, Automatic Detection of Geospatial Objects Using Multiple Hierarchical Segmentations, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.7, pp.2097-2111, 2008.
DOI : 10.1109/TGRS.2008.916644

W. Sun, V. Heidt, P. Gong, and G. Xu, Information fusion for rural land-use classification with high-resolution satellite imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.41, issue.4, pp.883-890, 2003.

M. J. Barnsley and S. L. Barr, Distinguishing urban land-use categories in fine spatial resolution land-cover data using a graph-based, structural pattern recognition system, Computers, Environment and Urban Systems, vol.21, issue.3-4, pp.209-225, 1997.
DOI : 10.1016/S0198-9715(97)10001-1

C. Kurtz, N. Passat, A. Puissant, and P. Gançarski, Hierarchical Segmentation of Multiresolution Remote Sensing Images, Proceedings of the 10th International Symposium on Mathematical Morphology -ISMM'11, pp.343-354, 2011.
DOI : 10.1109/TIP.2008.2002841
URL : https://hal.archives-ouvertes.fr/hal-01718349

L. Guigues, H. Le-men, and J. P. Cocquerez, The hierarchy of the cocoons of a graph and its application to image segmentation, Pattern Recognition Letters, vol.24, issue.8, pp.1059-1066, 2003.
DOI : 10.1016/S0167-8655(02)00252-0
URL : https://hal.archives-ouvertes.fr/hal-00706166

M. Pietikainen and A. Rosenfeld, Image segmentation by texture using pyramid node linking, IEEE Transactions on Systems, Man and Cybernetics, vol.11, issue.12, pp.822-825, 1981.
DOI : 10.21236/ADA098070
URL : http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA098070&Location=U2&doc=GetTRDoc.pdf

M. Pesaresi and J. A. Benediktsson, A new approach for the morphological segmentation of high-resolution satellite imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.39, issue.2, pp.309-320, 2001.
DOI : 10.1109/36.905239

J. Inglada and J. Michel, Qualitative Spatial Reasoning for High-Resolution Remote Sensing Image Analysis, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.2, pp.599-612, 2009.
DOI : 10.1109/TGRS.2008.2003435
URL : https://hal.archives-ouvertes.fr/hal-00594525

J. Shi and J. Malik, Normalized cuts and image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.8, pp.888-905, 2000.

R. Goffe, G. Damiand, and L. Brun, A Causal Extraction Scheme in Top-Down Pyramids for Large Images Segmentation, Lecture Notes in Computer Science, vol.6218, pp.264-274, 2010.
DOI : 10.1007/978-3-642-14980-1_25
URL : https://hal.archives-ouvertes.fr/hal-00567656

J. C. Tilton, Analysis of hierarchically related image segmentations, IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, 2003, pp.60-69, 2003.
DOI : 10.1109/WARSD.2003.1295173

M. Baatz and A. Schäpe, Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation, Angewandte Geographische Informations-Verarbeitung XII, pp.12-23, 2000.

J. M. 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

G. Scarpa, M. Haindl, and J. Zerubia, A Hierarchical Finite-State Model for Texture Segmentation, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, pp.1209-1212, 2007.
DOI : 10.1109/ICASSP.2007.366131
URL : http://hal.inria.fr/docs/00/12/07/92/PDF/RR-6066.pdf

J. C. Serra and P. Salembier, Connected operators and pyramids, Image Algebra and Morphological Image Processing IV, pp.65-76, 1993.
DOI : 10.1117/12.146672

P. Salembier and M. H. Wilkinson, Connected operators, IEEE Signal Processing Magazine, vol.26, issue.6, pp.136-157, 2009.
DOI : 10.1109/MSP.2009.934154
URL : http://arxiv.org/pdf/1710.04476

P. Salembier, A. Oliveras, and L. Garrido, Antiextensive connected operators for image and sequence processing, IEEE Transactions on Image Processing, vol.7, issue.4, pp.555-570, 1998.
DOI : 10.1109/83.663500
URL : http://upcommons.upc.edu/bitstream/2117/90134/1/UPC1.pdf

P. Monasse and F. Guichard, Scale-Space from a Level Lines Tree, Journal of Visual Communication and Image Representation, vol.11, issue.2, pp.224-236, 2000.
DOI : 10.1006/jvci.1999.0441

P. Salembier and L. Garrido, Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval, IEEE Transactions on Image Processing, vol.9, issue.4, pp.561-576, 2000.
DOI : 10.1109/83.841934
URL : http://gps-tsc.upc.es/imatge/pub/ps/IEEE_IP00_Salembier_Garrido.pdf

V. Vilaplana, F. Marques, and P. Salembier, Binary Partition Trees for Object Detection, IEEE Transactions on Image Processing, vol.17, issue.11, pp.2201-2216, 2008.
DOI : 10.1109/TIP.2008.2002841

S. Valero, P. Salembier, and J. Chanussot, New hyperspectral data representation using binary partition tree, 2010 IEEE International Geoscience and Remote Sensing Symposium, pp.80-83, 2010.
DOI : 10.1109/IGARSS.2010.5649780
URL : https://hal.archives-ouvertes.fr/hal-00578960

P. Soille, Constrained connectivity for hierarchical image partitioning and simplification, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.7, pp.1132-1145, 2008.
DOI : 10.1109/TPAMI.2007.70817

P. Soille, Constrained connectivity for the processing of very-high-resolution satellite images, International Journal of Remote Sensing, vol.31, issue.22, pp.5879-5893, 2010.
DOI : 10.1109/TGRS.2002.804618

S. Aksoy and H. G. Akcay, Multi-resolution segmentation and shape analysis for remote sensing image classification, Proceedings of 2nd International Conference on Recent Advances in Space Technologies, 2005. RAST 2005., pp.599-604, 2005.
DOI : 10.1109/RAST.2005.1512638

S. G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.7, pp.674-693, 1989.
DOI : 10.1109/34.192463

P. Scheunders and J. Sijbers, Multiscale watershed segmentation of multivalued images, Object recognition supported by user interaction for service robots, pp.855-858, 2002.
DOI : 10.1109/ICPR.2002.1048159
URL : http://www.ruca.ua.ac.be/visielab/sijbers/../papers/sijbers/icpr02a.pdf

J. B. Kim and H. J. Kim, Multiresolution-based watersheds for efficient image segmentation, Pattern Recognition Letters, vol.24, issue.1-3, pp.1-3, 2003.
DOI : 10.1016/S0167-8655(02)00270-2

Y. Chibani, Selective Synthetic Aperture Radar and Panchromatic Image Fusion by Using the ?? Trous Wavelet Decomposition, EURASIP Journal on Advances in Signal Processing, vol.2005, issue.14, pp.2207-2214, 2005.
DOI : 10.1155/ASP.2005.2207
URL : https://doi.org/10.1155/asp.2005.2207

Y. L. Chang, L. S. Liang, C. C. Han, J. P. Fang, W. Y. Liang et al., Multisource Data Fusion for Landslide Classification Using Generalized Positive Boolean Functions, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.6, pp.1697-1708, 2007.
DOI : 10.1109/TGRS.2007.895832

Z. Wang, D. Ziou, C. Armenakis, D. Li, and Q. Li, A comparative analysis of image fusion methods, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.6, pp.1391-1402, 2005.
DOI : 10.1109/TGRS.2005.846874

B. Aiazzi, S. Baronti, and M. Selva, Improving Component Substitution Pansharpening Through Multivariate Regression of MS $+$Pan Data, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.10, pp.3230-3239, 2007.
DOI : 10.1109/TGRS.2007.901007

R. Goffe, L. Brun, and G. Damiand, Tiled top-down combinatorial pyramids for large images representation, International Journal of Imaging Systems and Technology, vol.13, issue.1, pp.28-36, 2011.
DOI : 10.1109/34.88566
URL : https://hal.archives-ouvertes.fr/hal-00567701

S. Mallat, Wavelets for a vision, Proceedings of the IEEE, pp.604-614, 1996.
DOI : 10.1109/5.488702

C. Kurtz, N. Passat, P. Gançarski, and A. Puissant, Multi-resolution region-based clustering for urban analysis, International Journal of Remote Sensing, vol.1, issue.22, pp.5941-5973, 2010.
DOI : 10.1109/LGRS.2009.2020825
URL : https://hal.archives-ouvertes.fr/hal-01694411

L. Garrido, P. Salembier, and D. Garcia, Extensive operators in partition lattices for image sequence analysis, Signal Processing, vol.66, issue.2, pp.157-180, 1998.
DOI : 10.1016/S0165-1684(98)00004-8
URL : http://gps-tsc.upc.es/imatge/pub/ps/SP98_Garrido_Salembier_Garcia.ps.gz

A. J. Plaza and J. C. Tilton, Automated selection of results in hierarchical segmentations of remotely sensed hyperspectral images, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05., pp.946-4949, 2005.
DOI : 10.1109/IGARSS.2005.1526784

C. Wemmert, A. Puissant, G. Forestier, and P. Gançarski, Multiresolution Remote Sensing Image Clustering, IEEE Geoscience and Remote Sensing Letters, vol.6, issue.3, pp.533-537, 2009.
DOI : 10.1109/LGRS.2009.2020825
URL : https://hal.archives-ouvertes.fr/halshs-00520632

F. De-lussy, P. Kubik, D. Greslou, V. Pascal, P. Gigord et al., Pleiades-HR image system products and geometric accuracy, Proceedings of the ISPRS Hannover Workshop on High-Resolution Earth Imaging for Geospatial Information, pp.50-57, 2005.

S. H. Cha and S. N. Srihari, On measuring the distance between histograms, Pattern Recognition, vol.35, issue.6, pp.1355-1370, 2002.
DOI : 10.1016/S0031-3203(01)00118-2

H. Sakoe and S. Chiba, Dynamic programming algorithm optimization for spoken word recognition, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.26, issue.1, pp.43-49, 1978.
DOI : 10.1109/TASSP.1978.1163055

F. Petitjean, A. Ketterlin, and P. Gançarski, A global averaging method for dynamic time warping, with applications to clustering, Pattern Recognition, vol.44, issue.3, pp.678-693, 2011.
DOI : 10.1016/j.patcog.2010.09.013

R. Congalton, A review of assessing the accuracy of classifications of remotely sensed data, Remote Sensing of Environment, vol.37, issue.1, pp.35-46, 1991.
DOI : 10.1016/0034-4257(91)90048-B

J. Inglada, Automatic recognition of man-made objects in high resolution optical remote sensing images by SVM classification of geometric image features, ISPRS Journal of Photogrammetry and Remote Sensing, vol.62, issue.3, pp.236-248, 2007.
DOI : 10.1016/j.isprsjprs.2007.05.011