In this paper we propose to model the structural information in very high geometrical resolution optical images with morphological attribute filters. In particular we propose to perform a multilevel analysis based on different features of the image in contraposition to the use of conventional morphological profiles. We show how morphological attribute filters are conceptually and experimentally more capable to describe the characteristics of buildings with respect to morphological filters by reconstruction. Furthermore, we address the issue of selecting the most suitable parameters of the filters by proposing an architecture which embeds in the filtering procedure an optimization step based on genetic algorithms. The effectiveness of the proposed technique is stated by the experiments which were carried out on a panchromatic image acquired by the Quickbird satellite.
Modeling Structural Information for Building Extraction with Morphological Attribute Filters
Dalla Mura, Mauro;
2009-01-01
Abstract
In this paper we propose to model the structural information in very high geometrical resolution optical images with morphological attribute filters. In particular we propose to perform a multilevel analysis based on different features of the image in contraposition to the use of conventional morphological profiles. We show how morphological attribute filters are conceptually and experimentally more capable to describe the characteristics of buildings with respect to morphological filters by reconstruction. Furthermore, we address the issue of selecting the most suitable parameters of the filters by proposing an architecture which embeds in the filtering procedure an optimization step based on genetic algorithms. The effectiveness of the proposed technique is stated by the experiments which were carried out on a panchromatic image acquired by the Quickbird satellite.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
