Connected Component Trees for Multivariate Image Processing and Applications in Astronomy

Author

Perret, Benjamin ; Lefèvre, Sébastien ; Collet, Christophe ; Slezak, Eric

Author_Institution

LSIIT, Univ. of Strasbourg, Strasbourg, France

fYear

2010

fDate

23-26 Aug. 2010

Firstpage

4089

Lastpage

4092

Abstract

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 multispectral astronomical imaging: source separation and object detection.

Keywords

astronomical image processing; object detection; source separation; spectral analysis; trees (mathematics); astronomy; cc-tree; connected component trees; lattice theory; multispectral astronomical imaging; multivariate image processing; object detection; ordered set; source separation; Cost accounting; Image color analysis; Image reconstruction; Image segmentation; Imaging; Source separation; Astronomy; Connected Component Tree; Mathematical Morphology; Max-Tree; Multivariate Image Processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (ICPR), 2010 20th International Conference on

Conference_Location

Istanbul

ISSN

1051-4651

Print_ISBN

978-1-4244-7542-1

Type

conf

DOI

10.1109/ICPR.2010.994

Filename

5597711