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Proceedings Paper

Morphological segmentation/classification of vegetation cover types in remotely sensed images
Author(s): Teresa Barata; Pedro Pina; Isabel Granado
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Paper Abstract

A methodology based on mathematical morphology operators to classify vegetation cover types in remotely sensed images (ortho and satellite) is proposed in this paper. It consists on the automatic creation of the training sets by integrating the data extracted at higher spatial resolution with the corresponding data at higher spectral resolution, on the geometrical modelling of these sets to create a decision region for each class and on the automatic definition of the elementary units to be classified. The proposed approach is tested and illustrated with remotely sensed images from a region in centre Portugal.

Paper Details

Date Published: 19 January 2001
PDF: 11 pages
Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001); doi: 10.1117/12.413887
Show Author Affiliations
Teresa Barata, Instituto Superior Tecnico (Portugal)
Pedro Pina, Instituto Superior Tecnico (Portugal)
Isabel Granado, Instituto Superior Tecnico (Portugal)


Published in SPIE Proceedings Vol. 4170:
Image and Signal Processing for Remote Sensing VI
Sebastiano Bruno Serpico, Editor(s)

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