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, pp.898-916, 2011.

,

S. Beucher, Watershed, hierarchical segmentation and waterfall algorithm, Mathematical Morphology and Its Applications to Image Processing, vol.2, pp.69-76, 1994.

J. Cardelino, V. Caselles, M. Bertalmio, and G. Randall, A contrario selection of optimal partitions for image segmentation, SIAM Journal on Imaging Sciences, vol.6, issue.3, pp.1274-1317, 2013.

C. Couprie, C. Farabet, L. Najman, and Y. Lecun, Convolutional nets and watershed cuts for real-time semantic labeling of rgbd video, The Journal of Machine Learning Research, vol.15, pp.3489-3511, 2014.

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

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

J. Cousty, L. Najman, Y. Kenmochi, and S. Guimarães, Hierarchical segmentations with graphs: Quasi-flat zones, minimum spanning trees, and saliency maps, Journal of Mathematical Imaging and Vision, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01344727

J. Cousty, L. Najman, and B. Perret, Constructive links between some morphological hierarchies on edge-weighted graphs, Proceedings of 11th International Symposium on Mathematical Morphology -ISMM 2013, vol.7883, pp.86-97, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00798622

P. F. Felzenszwalb and D. P. Huttenlocher, Efficient graph-based image segmentation, International Journal of Computer Vision, vol.59, pp.167-181, 2004.

L. Guigues, J. P. Cocquerez, and H. L. Men, Scale-sets image analysis, International Journal of Computer Vision, vol.68, issue.3, pp.289-317, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00705364

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.
URL : https://hal.archives-ouvertes.fr/hal-00706166

S. J. Guimarães, J. Cousty, Y. Kenmochi, and L. Najman, A hierarchical image segmentation algorithm based on an observation scale, SSPR/SPR, pp.116-125, 2012.

S. J. Guimarães, Z. K. Do-patrocínio, Y. Kenmochi, J. Cousty, and L. Najman, Hierarchical image segmentation relying on a likelihood ratio test, Image Analysis and Processing -ICIAP 2015 -18th International Conference, vol.9280, pp.25-35, 2015.

Y. Haxhimusa, A. Ion, and W. G. Kropatsch, Irregular Pyramid Segmentations with Stochastic Graph Decimation Strategies, pp.277-286, 2006.

Y. Haxhimusa and W. Kropatsch, Hierarchy of partitions with dual graph contraction, Pattern Recognition, pp.338-345, 2003.

Y. Haxhimusa and W. G. Kropatsch, Segmentation graph hierarchies, Structural, Syntactic, and Statistical Pattern Recognition, vol.3138, pp.343-351, 2004.

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

M. S. Laurent-najman, Geodesic saliency of watershed contours and hierarchical segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.12, pp.1163-1173, 1996.

R. Marfil, L. Molina-tanco, A. Bandera, J. Rodríguez, and F. Sandoval, Pyramid segmentation algorithms revisited, Pattern Recognition, vol.39, issue.8, pp.1430-1451, 2006.

D. R. Martin, An empirical approach to grouping and segmentation, 2003.

D. R. Martin, C. C. Fowlkes, and J. Malik, Learning to detect natural image boundaries using local brightness, color, and texture cues, IEEE Trans. Pattern Anal. Mach. Intell, vol.26, issue.5, pp.530-549, 2004.

F. Meyer, The Dynamics of Minima and Contours, pp.329-336, 1996.

F. Meyer and P. Maragos, Morphological Scale-Space Representation with Levelings, pp.187-198, 1999.

O. J. Morris, M. J. Lee, and A. G. Constantinides, Graph theory for image analysis: an approach based on the shortest spanning tree. Communications, Radar and Signal Processing, IEE Proceedings F, vol.133, issue.2, pp.146-152, 1986.

P. F. Nacken, Image segmentation by connectivity preserving relinking in hierarchical graph structures, Pattern Recognition, vol.28, issue.6, pp.907-920, 1995.

L. Najman, On the equivalence between hierarchical segmentations and ultrametric watersheds, Journal of Mathematical Imaging and Vision, vol.40, pp.231-247, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00419373

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

T. Pavildis, Structural pattern recognition, 1977.

B. Perret, J. Cousty, J. C. Ura, and S. J. Guimarães, Evaluation of morphological hierarchies for supervised segmentation, Mathematical Morphology and Its Applications to Signal and Image Processing, pp.39-50, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01142072

J. Pont-tuset and F. Marqués, Measures and meta-measures for the supervised evaluation of image segmentation, Computer Vision and Pattern Recognition (CVPR), 2013.

J. Pont-tuset and F. Marques, Supervised evaluation of image segmentation and object proposal techniques, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015.

C. Ronse, Ordering partial partitions for image segmentation and filtering: Merging, creating and inflating blocks, Journal of Mathematical Imaging and Vision, vol.49, issue.1, pp.202-233, 2014.

P. Salembier and L. Garrido, Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval. Image Processing, IEEE Transactions on, vol.9, issue.4, pp.561-576, 2000.

J. Serra, A lattice approach to image segmentation, Journal of Mathematical Imaging and Vision, vol.24, issue.1, pp.83-130, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00622192

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

K. J. De-souza, A. De-albuquerque-araújo, Z. K. Do-patrocínio, and S. J. Guimarães, Graph-based hierarchical video segmentation based on a simple dissimilarity measure, Pattern Recognition Letters, vol.47, pp.85-92, 2014.

R. E. Tarjan, Efficiency of a good but not linear set union algorithm, Journal of the ACM, vol.22, issue.2, pp.215-225, 1975.

D. Varas, M. Alfaro, and F. Marqués, Multiresolution hierarchy co-clustering for semantic segmentation in sequences with small variations, ICCV -International Conference on Computer Vision, 2015.

Y. Xu, T. Géraud, and L. Najman, Connected filtering on tree-based shape-spaces, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.38, issue.6, pp.1126-1140, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01162437

C. T. Zahn, Graph-theoretical methods for detecting and describing gestalt clusters, IEEE Trans. Comput, vol.20, pp.68-86, 1971.