Patch-Based Mathematical Morphology for Image Processing, Segmentation and Classification

Olivier Lezoray (1)

1 Equipe Image - Laboratoire GREYC - UMR6072

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]

Olivier Lezoray. Patch-Based Mathematical Morphology for Image Processing, Segmentation and Classification. Advanced Concepts for Intelligent Vision Systems, 2015, Catane, Italy. pp.46-57, ⟨10.1007/978-3-319-25903-1_5⟩. ⟨hal-01252874⟩