Graph-based morphological processing of multivariate microscopy images and data bases

Authors:
O. Lézoray
Affiliations:
Université de Caen Basse-Normandie, GREYC UMR CNRS, Caen Cedex, France
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

Citing 7
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Abstract

The extension of lattice based operators to manifolds is still a challenging theme in mathematical morphology. In this paper, we propose to explicitly construct complete lattices and replace each element of a manifold by its rank suitable for classical morphological processing. Manifold learning is considered as the basis for the construction of a complete lattice. The whole processing of multivariate functions is expressed on graphs to have a formalism that can be applied on images, region adjacency graphs, and image databases. Several examples in microscopy do illustrate the benefits of the proposed approach.