Title :
Improvement of Land Cover Map from Satellite Imagery using DST and DSmT
Author :
Khedam, Radja ; Bouakache, Abdenour ; Mercier, Gregoire ; Belhadj-Aissa, Aichouche
Author_Institution :
Fac. of Electron. & Comput. Sci., Univ. of Sci. & Technol. Houari Boumediene, Algiers
Abstract :
The aim of this paper is to show that Dempster-Shafer theory (DST) and a recent theory of plausible and paradoxical reasoning introduced by Dezert and Smaradache and thus called Dezert-Smarandache theory (DSmT), can be successfully applied to improve a supervised classification of remotely sensed data. Notice that application fields of these two theories are related on multisensor/multitemporal/multiscale data fusion. In this study, our contribution lies in developing a new multispectral data classification process which can be seen as a multisensor fusion process where each thematic class is considered as one source of information
Keywords :
image classification; inference mechanisms; sensor fusion; Dempster-Shafer theory; Dezert-Smarandache theory; land cover map; multisensor data fusion; multispectral data classification; paradoxical reasoning; remotely data sensing; satellite imagery; supervised classification; Bayesian methods; Classification algorithms; Computer science; Image processing; Information resources; Laboratories; Mathematical model; Remote monitoring; Satellites; Uncertainty;
Conference_Titel :
Information and Communication Technologies, 2006. ICTTA '06. 2nd
Conference_Location :
Damascus
Print_ISBN :
0-7803-9521-2
DOI :
10.1109/ICTTA.2006.1684400
