Merge-and-simplify operation for compact combinatorial pyramid definition

Guillaume Damiand 1 Florence Zara 2
1 M2DisCo - Geometry Processing and Constrained Optimization
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 SAARA - Simulation, Analyse et Animation pour la Réalité Augmentée
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Image pyramids are employed for years in digital image processing. They permit to store and use different scales/levels of details of an image. To represent all the topological information of the different levels, combinatorial pyramids have proved having many interests. But, when using an explicit representation, one drawback of this structure is the memory space required to store such a pyramid. In this paper, this drawback is solved by defining a compact version of combinatorial pyramids. This definition is based on the definition of a new operation, called "merge-and-simplify", which simultaneously merges regions and simplifies their boundaries. Our experiments show that the memory space of our solution is much smaller than the one of the original version. Moreover, the computation time of our solution is faster, because there are less levels in our pyramid than in the original one.
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Guillaume Damiand, Florence Zara. Merge-and-simplify operation for compact combinatorial pyramid definition. Pattern Recognition Letters, Elsevier, 2020, 129, pp.48-55. ⟨10.1016/j.patrec.2019.11.009⟩. ⟨hal-02389912⟩

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