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Article Dans Une Revue Journal of Mathematical Imaging and Vision Année : 2023

Morphological Hierarchies: A Unifying Framework with New Trees

Résumé

Morphological hierarchies constitute a rich and powerful family of graph-based structures that can be used for image modeling, processing and analysis. In this article, we focus on an important subfamily of morphological hierarchies, namely the trees that model partial partitions of the image support. This subfamily includes in particular the component-tree and the tree of shapes. In this context, we provide some new graph-based structures (one directed acyclic graph and three trees): the graph of valued shapes, the tree of valued shapes, the complete tree of shapes and the topological tree of shapes. These new objects create a continuum between the two notions of component-tree and tree of shapes. In particular, they allow to establish that these two trees (together with a third notion of adjacency tree generally considered in topological image analysis) can be defined and handled in a unified framework. In addition, this framework enables to enrich the component-tree with additional information, leading on the one hand to a topological description of grey-level images that relies on the same paradigm as persistent homology, and on the other hand to the proposal of a topological version of tree of shapes. This article provides a theoretical analysis of these new morphological hierarchies and their links with the usual ones. It also proposes an algorithmic description of two ways of building these new morphological hierarchies, and a discussion on the links that exist between these morphological hierarchies and certain topological invariants and descriptors.
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Dates et versions

hal-04137677 , version 1 (15-09-2023)

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Nicolas Passat, Julien Mendes Forte, Yukiko Kenmochi. Morphological Hierarchies: A Unifying Framework with New Trees. Journal of Mathematical Imaging and Vision, 2023, 65 (5), pp.718-753. ⟨10.1007/s10851-023-01154-x⟩. ⟨hal-04137677⟩
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