Patch-Based Mathematical Morphology for Image Processing, Segmentation and Classification
Résumé
In this paper, a new formulation of patch-based adap-tive mathematical morphology is addressed. In contrast to classical approaches, the shape of structuring elements is not modified but adap-tivity is directly integrated into the definition of a patch-based complete lattice. The manifold of patches is learned with a nonlinear bijective mapping , interpreted in the form of a learned rank transformation together with an ordering of vectors. This ordering of patches relies on three steps: dictionary learning, manifold learning and out of sample extension. The performance of the approach is illustrated with innovative examples of patch-based image processing, segmentation and texture classification.
Domaines
Traitement des images [eess.IV]
Fichier principal
Lezoray_ACIVS2015 (1).pdf (1.47 Mo)
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Lezoray_ACIVS2015.pdf (6.63 Mo)
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Origine | Fichiers produits par l'(les) auteur(s) |
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Origine | Fichiers produits par l'(les) auteur(s) |
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