Nonlocal PDEs-based Morphology on Weighted Graphs for Image and Data Processing

Vinh Thong Ta (1) , Abderrahim Elmoataz (2) , Olivier Lezoray (2)

1 LaBRI - Laboratoire Bordelais de Recherche en Informatique
2 Equipe Image - Laboratoire GREYC - UMR6072

Mathematical morphology (MM) offers a wide range of operators to address various image processing problems. These operators can be defined in terms of algebraic (discrete) sets or as partial differential equations (PDEs). In this paper, we intro- duce a nonlocal PDEs-based morphological framework defined on weighted graphs. We present and analyze a set of operators that leads to a family of discretized morphological PDEs on weighted graphs. Our formulation introduces nonlocal patch-based configurations for image processing and extends PDEs-based approach to the processing of arbitrary data such as nonuniform high di- mensional data. Finally, we show the potentialities of our methodology in order to process, segment and classify images and arbitrary data.

Domaines: Traitement des images [eess.IV]

Vinh Thong Ta, Abderrahim Elmoataz, Olivier Lezoray. Nonlocal PDEs-based Morphology on Weighted Graphs for Image and Data Processing. IEEE Transactions on Image Processing, 2011, 26 (2), pp.1504-1516. ⟨10.1109/TIP.2010.2101610⟩. ⟨hal-00708975⟩