Hierarchical segmentations with graphs: quasi-flat zones, minimum spanning trees, and saliency maps

Abstract : Hierarchies of partitions are generally represented by dendrograms (direct representation). They can also be represented by saliency maps or minimum spanning trees. In this article, we precisely study the links between these three representations. In particular, we provide a new bijection between saliency maps and hierarchies based on quasi-flat zones as often used in image processing and we characterize saliency maps and minimum spanning trees as solutions to constrained minimization problems where the constraint is quasi-flat zones preservation. In practice, these results make up a toolkit for designing new hierarchical methods where one can choose the most convenient representation. They also invite us to process non-image data with morphological hierarchies. More precisely, we show the practical interest of the proposed framework for: i) hierarchical watershed image segmentations, ii) combinations of dierent hierarchical segmentations, iii) hierarchicalizations of some non-hierarchical image segmentation methods based on regional dissimilarities, and iv) hierarchical analysis of geographical data.
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Journal of Mathematical Imaging and Vision, Springer Verlag, 2017
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Dernière modification le : mardi 12 décembre 2017 - 08:20:24

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  • HAL Id : hal-01344727, version 2

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Jean Cousty, Laurent Najman, Yukiko Kenmochi, Silvio Guimarães. Hierarchical segmentations with graphs: quasi-flat zones, minimum spanning trees, and saliency maps. Journal of Mathematical Imaging and Vision, Springer Verlag, 2017. 〈hal-01344727v2〉

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