R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua et al., SLIC Superpixels Compared to State-of-the-Art Superpixel Methods, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.11, pp.2274-2282, 2012.
DOI : 10.1109/TPAMI.2012.120

S. Alpert, M. Galun, A. Brandt, and R. Basri, Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.2, pp.315-327, 2012.
DOI : 10.1109/TPAMI.2011.130

P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik, Contour Detection and Hierarchical Image Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.5, pp.898-916, 2011.
DOI : 10.1109/TPAMI.2010.161

P. Arbeláez and L. Cohen, A Metric Approach to Vector-Valued Image Segmentation, International Journal of Computer Vision, vol.133, issue.2, pp.119-126, 2006.
DOI : 10.1109/34.44407

M. Bender and M. Farach-colton, The LCA Problem Revisited, pp.88-94, 2000.
DOI : 10.1007/10719839_9

G. Bertrand, On Topological Watersheds, Journal of Mathematical Imaging and Vision, vol.34, issue.6, pp.217-230, 2005.
DOI : 10.1109/34.87344

URL : https://hal.archives-ouvertes.fr/hal-00622398

S. Beucher, Watershed, Hierarchical Segmentation and Waterfall Algorithm, Mathematical Morphology and its Applications to Image and Signal Processing, pp.69-76, 1994.
DOI : 10.1007/978-94-011-1040-2_10

M. Couprie, L. Najman, and G. Bertrand, Quasi-Linear Algorithms for the Topological Watershed, Journal of Mathematical Imaging and Vision, vol.13, issue.6, pp.231-249, 2005.
DOI : 10.1007/s10851-005-4892-4

URL : https://hal.archives-ouvertes.fr/hal-00622399

J. Cousty, G. Bertrand, L. Najman, and M. Couprie, Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.8, pp.1362-1374, 2009.
DOI : 10.1109/TPAMI.2008.173

URL : https://hal.archives-ouvertes.fr/hal-00622410

J. Cousty and L. Najman, Incremental Algorithm for Hierarchical Minimum Spanning Forests and Saliency of Watershed Cuts, Mathematical Morphology and its Applications to Image and Signal Processing, pp.272-283, 2011.
DOI : 10.1109/T-C.1971.223083

URL : https://hal.archives-ouvertes.fr/hal-00622505

J. Cousty, L. Najman, Y. Kenmochi, and S. Guimarães, New Characterizations of Minimum Spanning Trees and of Saliency Maps Based on Quasi-flat Zones, Mathematical Morphology and Its Applications to Signal and Image Processing, pp.205-216, 2015.
DOI : 10.1007/978-3-319-18720-4_18

URL : https://hal.archives-ouvertes.fr/hal-01148958

J. Cousty, L. Najman, and B. Perret, Constructive Links between Some Morphological Hierarchies on Edge-Weighted Graphs, Mathematical Morphology and its Applications to Image and Signal Processing, pp.86-97, 2013.
DOI : 10.1007/978-3-642-38294-9_8

URL : https://hal.archives-ouvertes.fr/hal-00798622

J. Cousty, L. Najman, and J. Serra, Raising in watershed lattices, 2008 15th IEEE International Conference on Image Processing, pp.2196-2199, 2008.
DOI : 10.1109/ICIP.2008.4712225

URL : https://hal.archives-ouvertes.fr/hal-00622472

P. Felzenszwalb and D. Huttenlocher, Efficient Graph-Based Image Segmentation, International Journal of Computer Vision, vol.59, issue.2, pp.167-181, 2004.
DOI : 10.1023/B:VISI.0000022288.19776.77

A. D. Gordon, A Review of Hierarchical Classification, Journal of the Royal Statistical Society. Series A (General), vol.150, issue.2, pp.119-137, 1987.
DOI : 10.2307/2981629

L. Guigues, J. P. Cocquerez, and H. L. Men, Scale-Sets Image Analysis, International Journal of Computer Vision, vol.20, issue.6, pp.289-317, 2006.
DOI : 10.1109/34.56205

URL : https://hal.archives-ouvertes.fr/hal-00705364

S. J. Guimarães, J. Cousty, Y. Kenmochi, and L. Najman, A Hierarchical Image Segmentation Algorithm Based on an Observation Scale, pp.116-125, 2012.
DOI : 10.1007/978-3-642-34166-3_13

S. Guimarães, Y. Kenmochi, J. Cousty, Z. Patrocínio-jr, and L. Najman, Hierarchizing graph-based image segmentation algorithms relying on region dissimilarity the case of the Felzenszwalb-Huttenlocher method (2016) URL https

S. J. Guimarães, K. G. Patrocínio-zenilton, and J. , A Graph-Based Hierarchical Image Segmentation Method Based on a Statistical Merging Predicate, Image Analysis and Processing -ICIAP 2013, pp.11-20, 2013.
DOI : 10.1007/978-3-642-41181-6_2

S. J. Guimarães, G. Do-patrocínio-zenilton-kleber, J. Kenmochi, Y. Cousty, J. Najman et al., Hierarchical Image Segmentation Relying on a Likelihood Ratio Test, Image Analysis and Processing -ICIAP 2015, pp.25-35, 2015.
DOI : 10.1007/978-3-319-23234-8_3

B. R. Kiran and J. Serra, Fusion of ground truths and hierarchies of segmentations, Pattern Recognition Letters, vol.47, pp.63-71, 2014.
DOI : 10.1016/j.patrec.2014.04.019

B. R. Kiran and J. Serra, Global???local optimizations by hierarchical cuts and climbing energies, Pattern Recognition, vol.47, issue.1, pp.12-24, 2014.
DOI : 10.1016/j.patcog.2013.05.012

URL : https://hal.archives-ouvertes.fr/hal-00802978

V. A. Kovalevsky, Finite topology as applied to image analysis, Computer Vision, Graphics, and Image Processing, vol.46, issue.2, pp.141-161, 1989.
DOI : 10.1016/0734-189X(89)90165-5

B. Leclerc, Description combinatoire des ultramétriques, Mathématiques et Sciences humaines, vol.73, pp.5-37, 1981.

F. Malmberg and C. L. Hendriks, An efficient algorithm for exact evaluation of stochastic watersheds, Pattern Recognition Letters, vol.47, pp.80-84, 2014.
DOI : 10.1016/j.patrec.2014.03.016

D. R. Martin, C. C. Fowlkes, and J. Malik, Learning to detect natural image boundaries using local brightness, color, and texture cues, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.5, pp.530-549, 2004.
DOI : 10.1109/TPAMI.2004.1273918

F. Meyer, The Dynamics of Minima and Contours, Mathematical Morphology and its Applications to Image and Signal Processing, pp.329-336, 1996.
DOI : 10.1007/978-1-4613-0469-2_38

F. Meyer and P. Maragos, Morphological Scale-Space Representation with Levelings, Lecture Notes in Computer Science, vol.1682, pp.187-198, 1999.
DOI : 10.1007/3-540-48236-9_17

URL : http://cvsp.cs.ntua.gr/publications/confr/MeyerMaragos_MorphologicalSSLevelings_SS1999.pdf

F. Meyer and L. Najman, Segmentation, minimum spanning tree and hierarchies. Mathematical morphology: from theory to applications pp, pp.229-261, 2013.
DOI : 10.1002/9781118600788.ch9

URL : https://hal.archives-ouvertes.fr/hal-00622502

P. Monasse and F. Guichard, Fast computation of a contrast-invariant image representation, IEEE Transactions on Image Processing, vol.9, issue.5, pp.860-872, 2000.
DOI : 10.1109/83.841532

M. Nagao, T. Matsuyama, and Y. Ikeda, Region extraction and shape analysis in aerial photographs, Computer Graphics and Image Processing, vol.10, issue.3, pp.195-223, 1979.
DOI : 10.1016/0146-664X(79)90001-7

L. Najman, On the Equivalence Between Hierarchical Segmentations and??Ultrametric Watersheds, Journal of Mathematical Imaging and Vision, vol.113, issue.3, pp.231-247, 2011.
DOI : 10.1007/10719839_9

URL : https://hal.archives-ouvertes.fr/hal-00419373

L. Najman, J. Cousty, and B. Perret, Playing with Kruskal: Algorithms for Morphological Trees in Edge-Weighted Graphs, Mathematical Morphology and its Applications to Image and Signal Processing, pp.135-146, 2013.
DOI : 10.1007/978-3-642-38294-9_12

URL : https://hal.archives-ouvertes.fr/hal-00798621

L. Najman and M. Schmitt, Geodesic saliency of watershed contours and hierarchical segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.12, pp.1163-1173, 1996.
DOI : 10.1109/34.546254

URL : https://hal.archives-ouvertes.fr/hal-00622128

J. P. Nakache and J. Confais, Approche pragmatique de la classification: arbres hiérarchiques, partitionnements, Editions Technip, 2004.

R. Nock and F. Nielsen, Statistical region merging, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.11, pp.1452-1458, 2004.
DOI : 10.1109/TPAMI.2004.110

URL : http://www.univ-ag.fr/~rnock/Articles/Drafts/tpami04-nn.pdf

T. Pavlidis, Structural pattern recognition, 1977.
DOI : 10.1007/978-3-642-88304-0

B. Peng, L. Zhang, and D. Zhang, Automatic Image Segmentation by Dynamic Region Merging, IEEE Transactions on Image Processing, vol.20, issue.12, pp.3592-3605, 2011.
DOI : 10.1109/TIP.2011.2157512

S. Philipp-foliguet, M. Jordan, L. Najman, and J. Cousty, Artwork 3D model database indexing and classification, Pattern Recognition, vol.44, issue.3, pp.588-597, 2011.
DOI : 10.1016/j.patcog.2010.09.016

URL : https://hal.archives-ouvertes.fr/hal-00538470

C. Ronse, Ordering Partial Partitions for Image Segmentation and Filtering: Merging, Creating and Inflating Blocks, Journal of Mathematical Imaging and Vision, vol.30, issue.7, pp.202-233, 2014.
DOI : 10.1109/TPAMI.2007.70817

C. Rother, V. Kolmogorov, and A. Blake, "GrabCut", ACM Transactions on Graphics, vol.23, issue.3, pp.309-314, 2004.
DOI : 10.1145/1015706.1015720

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

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://gps-tsc.upc.es/imatge/pub/ps/IEEE_IP98_Salembier_Oliveras_Garrido.ps.gz

S. Jr, C. N. Freitas, and A. A. , A survey of hierarchical classification across different application domains, Data Mining and Knowledge Discovery, vol.22, issue.12, pp.31-72, 2011.

A. Skupin, The world of geography: Visualizing a knowledge domain with cartographic means, Proceedings of the National Academy of Sciences, vol.37, issue.Supplement 1, pp.5274-5278, 2004.
DOI : 10.1007/3-540-36222-3_11

A. Skupin and S. I. Fabrikant, Spatialization Methods: A Cartographic Research Agenda for Non-geographic Information Visualization, Cartography and Geographic Information Science, vol.30, issue.2, pp.99-119, 2003.
DOI : 10.1559/152304003100011081

URL : http://www.geog.ucsb.edu/~sara/html/research/pubs/skupin_fabrikant_cagis.pdf

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 and L. Najman, On Morphological Hierarchical Representations for Image Processing and Spatial Data Clustering, Applications of Discrete Geometry and Mathematical Morphology: First International Workshop, WADGMM 2010, pp.43-67, 2010.
DOI : 10.1007/978-3-642-32313-3_4

URL : https://hal.archives-ouvertes.fr/hal-00733251

E. Urbach, J. Roerdink, and M. Wilkinson, Connected Shape-Size Pattern Spectra for Rotation and Scale-Invariant Classification of Gray-Scale Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.2, pp.272-285, 2007.
DOI : 10.1109/TPAMI.2007.28

C. Vachier and F. Meyer, Extinction value: a new measurement of persistence, IEEE Workshop on Nonlinear Signal and Image Processing, pp.254-257, 1995.