Published 2010 | Version v1
Conference paper Metadata-only

Connected component trees for multivariate image processing applications in astronomy

Perret, Benjamin
Lefèvre, Sébastien
Collet, Christophe
Slezak, Eric
Others:
Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection (LSIIT) ; Centre National de la Recherche Scientifique (CNRS)
Laboratoire de Cosmologie, Astrophysique Stellaire & Solaire, de Planétologie et de Mécanique des Fluides (CASSIOPEE) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS)

Description

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.

Abstract

International audience

Additional details

Identifiers Origin repository
Created:
December 4, 2022
Modified:
November 28, 2023