Abstract
This article presents a technique that arranges the elements of hierarchical representations of images according to a coarseness attribute. The choice of the attribute can be made according to prior knowledge about the content of the images and the intended application. The transformation is similar to filtering a hierarchy with a non-increasing attribute, and comprises the results of multiple simple filterings with an increasing attribute. The transformed hierarchy can be used for search space reduction prior to the image analysis process because it allows for direct access to the hierarchy elements at the same scale or a narrow range of scales.
Chapter PDF
Similar content being viewed by others
Keywords
References
Cousty, J., Najman, L.: Incremental Algorithm for Hierarchical Minimum Spanning Forests and Saliency of Watershed Cuts. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds.) ISMM 2011. LNCS, vol. 6671, pp. 272–283. Springer, Heidelberg (2011)
Gueguen, L., Soille, P.: Frequent and Dependent Connectivities. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds.) ISMM 2011. LNCS, vol. 6671, pp. 120–131. Springer, Heidelberg (2011)
Jones, R.: Connected Filtering and Segmentation using Component Trees. Computer Vision and Image Understanding 75(3), 215–228 (1999)
Monasse, P., Guichard, F.: Fast Computation of a Contrast-Invariant Image Representation. IEEE Transactions on Image Processing 9(5), 860–872 (2000)
Najman, L.: On the Equivalence Between Hierarchical Segmentations and Ultrametric Watersheds. JMIV 40(3), 231–247 (2011)
Najman, L., Couprie, M.: Building the Component Tree in Quasi-Linear Time. IEEE Transactions on Image Processing 15(11), 3531–3539 (2006)
Soille, P., Najman, L.: On Morphological Hierarchical Representations for Image Processing and Spatial Data Clustering. In: Köthe, U., Montanvert, A., Soille, P. (eds.) WADGMM 2010. LNCS, vol. 7346, pp. 43–67. Springer, Heidelberg (2012)
Ouzounis, G., Wilkinson, M.: Mask-Based Second-Generation Connectivity and Attribute Filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(6), 990–1004 (2007)
Ouzounis, G.K., Soille, P.: Pattern Spectra from Partition Pyramids and Hierarchies. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds.) ISMM 2011. LNCS, vol. 6671, pp. 108–119. Springer, Heidelberg (2011)
Salembier, P., Garrido, L.: Binary Partition Tree as an Efficient Representation for Image Processing, Segmentation, and Information Retrieval. IEEE Transactions on Image Processing 9(4), 561–576 (2000)
Salembier, P., Oliveras, A., Garrido, L.: Antiextensive Connected Operators for Image and Sequence Processing. IEEE Transactions on Image Processing 7(4), 555–570 (1998)
Salembier, P., Wilkinson, M.H.F.: Connected Operators. IEEE Signal Processing Magazine 26(6), 136–157 (2009)
Serra, J.C., Salembier, P.: Connected operators and pyramids. In: Dougherty, E.R., Gader, P.D., Serra, J.C. (eds.) Image Algebra and Morphological Image Processing IV. SPIE, vol. 2030, pp. 65–76. SPIE Press, San Diego (1993)
Soille, P.: Morphological Image Analysis: Principles and Applications, 2nd edn. Springer, New York (2003)
Soille, P.: On Genuine Connectivity Relations Based on Logical Predicates. In: Proc. of the 14th Int. Conf. on Image Analysis and Processing, pp. 487–492. IEEE Computer Society Press, Los Alamitos (2007)
Soille, P.: Constrained Connectivity for Hierarchical Image Partitioning and Simplification. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(7), 1132–1145 (2008)
Soille, P.: Preventing Chaining Through Transitions While Favouring It within Homogeneous Regions. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds.) ISMM 2011. LNCS, vol. 6671, pp. 96–107. Springer, Heidelberg (2011)
Soille, P., Grazzini, J.: Constrained Connectivity and Transition Regions. In: Wilkinson, M.H.F., Roerdink, J.B.T.M. (eds.) ISMM 2009. LNCS, vol. 5720, pp. 59–69. Springer, Heidelberg (2009)
Song, Y.: A Topdown Algorithm for Computation of Level Line Trees. IEEE Transactions on Image Processing 16(8), 2107–2116 (2007)
Song, Y., Zhang, A.: Locating Image Background by Monotonic Tree. In: Caulfield, H., Chen, S.H., Cheng, H.D., Duro, R., Honovar, V., Kerre, E.E., Lu, M., Romay, M., Shih, T., Ventura, D., Wang, P., Yang, Y. (eds.) 6th Joint Conf. on Information Sciences, pp. 879–884. Association for Intelligent Machinery, Inc., Durham (2002)
Song, Y., Zhang, A.: Analyzing scenery images by monotonic tree. ACM Multimedia Systems J. 8(6), 495–511 (2003)
Vilaplana, V., Marques, F., Salembier, P.: Binary Partition Trees for Object Detection. IEEE Transactions on Image Processing 17(11), 2201–2216 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bosilj, P., Lefèvre, S., Kijak, E. (2013). Hierarchical Image Representation Simplification Driven by Region Complexity. In: Petrosino, A. (eds) Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41181-6_57
Download citation
DOI: https://doi.org/10.1007/978-3-642-41181-6_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41180-9
Online ISBN: 978-3-642-41181-6
eBook Packages: Computer ScienceComputer Science (R0)
