A morphological approach for feature space partitioning

Author

Barata, Teresa ; Pina, Pedro

Author_Institution

Geo-Syst. Centre, Inst. Superior Tecnico, Lisbon, Portugal

Volume

3

Issue

1

fYear

2006

Firstpage

173

Lastpage

177

Abstract

A mathematical morphology-based methodology to construct decision region borders that geometrically model the training sets of points is presented in this letter. It is shown that the incorporation of the geometric features of the training sets leads to higher classification rates. Our approach is illustrated with two features of seven land-cover classes [forest (3), soil (2), vegetation, and water] constructed from remotely sensed images of a region in the center of Portugal.

Keywords

feature extraction; geophysical signal processing; geophysical techniques; image texture; remote sensing; Portugal; anisotropic distance function; classification rates; decision region borders; directional structuring elements; feature space partitioning; forestry; geometric features; land-cover classes; mathematical morphology-based methodology; remotely sensed images; training sets; vegetation; Costs; Helium; Mathematical model; Satellites; Shape; Soil; Solid modeling; Spatial resolution; Testing; Vegetation mapping; Anisotropic distance function; decision region borders; directional structuring elements; textural units;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2005.861539

Filename

1576714