Title :
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
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;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.994