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Communication Dans Un Congrès Année : 2021

On Morphological Hierarchies for Image Sequences

Résumé

Morphological hierarchies form a popular framework aiming at emphasizing the multiscale structure of digital image by performing an unsupervised spatial partitioning of the data. These hierarchies have been recently extended to cope with image sequences, and different strategies have been proposed to allow their construction from spatio-temporal data. In this paper, we compare these hierarchical representation strategies for image sequences according to their structural properties. We introduce a projection method to make these representations comparable. Furthermore, we extend one of these recent strategies in order to obtain more efficient hierarchical representations for image sequences. Experiments were conducted on both synthetic and real datasets, the latter being made of satellite image time series. We show that building one hierarchy by using spatial and temporal information together is more efficient comparing to other existing strategies.
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Dates et versions

hal-03291870 , version 1 (23-07-2021)

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Citer

Caglayan Tuna, Alain Giros, François Merciol, Sébastien Lefèvre. On Morphological Hierarchies for Image Sequences. ICPR 2020 – 25th International Conference on Pattern Recognition, Jan 2021, Milan (virtual), Italy. pp.1-8, ⟨10.1109/ICPR48806.2021.9412177⟩. ⟨hal-03291870⟩
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