This paper proposes an approach referred as: iterative refinement of possibility distributions
by learning (IRPDL) for pixel-based image classification. The IRPDL approach is based on …

La phase de segmentation constitue un point central dans les processus d'interprétation et
d'analyse d'images. Bien que la segmentation ait déjà fait l'objet de nombreux travaux, elle …

Remote‐sensing data have proved to be a valuable source of land cover information,
especially when looking at larger areas. In this study, multi‐temporal NOAA‐AVHRR data …

The strong impact of land use on the climatic and hydrological cycle necessitates a detailed
knowledge of the land use/land cover for land surface modelling. Within the research project …

Abstract Information processing in modern pattern recognition systems is becoming
increasingly complex due to the flood of data and the need to deal with different aspects of …

The integration of multi-source ancillary data is one of the most promising techniques for
improved classification of remote sensing images. In this research a classification strategy …

To model the impact of the landcover on the climatic and hydrological cycles, an exact
knowledge of two facts is necessary: the landuse and the amount of biomass. The study …

In this paper we present a possibilistic classifier of multispectral remotely sensed images.
This classifier developed in the framework of possibility theory is based on a fusion process …

Увеличение объема аэрокосмической информации, обрабатываемой в целях решения
социально-экономических задач, обуславливает необходимость автоматизации …

Cette thèse s' inscrit dans le contexte de la représentation et du traitement possibiliste des
connaissances en vue de concevoir un système d'interprétation de scène observée par de …