Connected component trees for multivariate image processing applications in astronomy

Benjamin Perret (1) , Sébastien Lefèvre (1) , Christophe Collet (1) , Eric Slezak (2)

1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 CASSIOPEE - Laboratoire de Cosmologie, Astrophysique Stellaire & Solaire, de Planétologie et de Mécanique des Fluides

In this paper, we investigate the possibilities offered by the extension of the connected component trees (cc-trees) to multivariate images. We propose a general framework for image processing using the cc-tree based on the lattice theory and we discuss the possible applications depending on the properties of the underlying ordered set. This theoretical reflexion is illustrated by two applications in mul-tispectral astronomical imaging: source separation and object detection.

Domaines: Traitement des images [eess.IV]

Benjamin Perret, Sébastien Lefèvre, Christophe Collet, Eric Slezak. Connected component trees for multivariate image processing applications in astronomy. 20th IAPR International Conference on Pattern Recognition (ICPR), 2010, Istanbul, Turkey. pp.4089-4092. ⟨hal-00516044⟩