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A morphological approach for feature space partitioning

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2 Author(s)
Barata, T. ; Geo-Syst. Centre, Inst. Superior Tecnico, Lisbon, Portugal ; Pina, P.

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.

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Geoscience and Remote Sensing Letters, IEEE  (Volume:3 ,  Issue: 1 )