Title :
Removing ambiguities in a multispectral image classification
Author :
Mathieu-Marni, Sandrine ; Leymarie, Pierre ; Berthod, Marc
Author_Institution :
Inst. Nat. de Recherche en Inf. et Autom., Sophia-Antipolis, France
Abstract :
This article deals with the processing of already classified satellite images according to land use in order to remove ambiguities, i.e. mistakes in labels. Those images have already been classified with the maximum likehood method but some classes are not correctly determined. For the elimination of ambiguities in this kind of class, the authors applied their method of determination of land use mixture in pixels. They first briefly review their method of determination of land use mixture. Then they explain how they deal with ambiguities in labels of the maximum likehood classification. They finish with three examples of satellite images that have not correctly been classified. The first one is the vineyard case. Another example for bare soil and urban zone. The last one is a forestry survey application, the determination of the planted pines density
Keywords :
forestry; geophysical signal processing; geophysical techniques; image classification; optical information processing; agriculture; ambiguity removal; bare soil; classified satellite image; forest; forestry; geophysical measurement technique; label mistake; land use; maximum likehood method; multispectral image classification; optical imaging; planted pines; terrain mapping; tree density; urban zone; vegetation mapping; vineyard; visible infrared satellite remote sensing; Clouds; Forestry; Image resolution; Independent component analysis; Layout; Multispectral imaging; Pixel; Radiometry; Satellite broadcasting; Soil;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
Conference_Location :
Firenze
Print_ISBN :
0-7803-2567-2
DOI :
10.1109/IGARSS.1995.524066