On the Complementarity of an Ontology and a Nearest Neighbour Classifier for Remotely Sensed Image Interpretation

Sébastien Derivaux (1) , Nicolas Durand (2) , Cédric Wemmert (1)

1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection

Automatic image interpretation could be achieved by first performing a segmentation of the image, i.e. aggregating similar pixels to form regions, then use a region-based classification. This paper presents two region-based classifications, namely a supervised classification and an ontology-based classification and discuss their pros and cons. As they are complementary, we propose to combine these two approaches. Results shown that the presented method is relevant.

Domaines: Apprentissage [cs.LG]

Sébastien Derivaux, Nicolas Durand, Cédric Wemmert. On the Complementarity of an Ontology and a Nearest Neighbour Classifier for Remotely Sensed Image Interpretation. International Geoscience and Remote Sensing Symposium (IGARSS 2007), 2007, Barcelona, Spain. pp.3983 - 3986, ⟨10.1109/IGARSS.2007.4423093⟩. ⟨hal-01463171⟩