Title : 
A new mass functions assignment in the Dempster-Shafer theory : the fuzzy statistical approach
         
        
            Author : 
Germain, M. ; Boucher, J.-M. ; Benie, G.B.
         
        
            Author_Institution : 
Ecole Nat. Super. des Telecommun. de Bretagne, Brest
         
        
        
        
        
        
            Abstract : 
This paper describes a new analysis of the evidential reasoning based on the fuzzy statistical approach. The evidential reasoning uses the Dempster-Shafer (DS) theory with a new approach to assign the mass functions. We test the proposed method on a basic simulated noisy fuzzy image composed on three pure classes, and we compare the mass functions representation with standard statistical methods and fuzzy methods. For a real study, we apply the new data fusion process to remote sensing data fusion.
         
        
            Keywords : 
case-based reasoning; fuzzy set theory; inference mechanisms; sensor fusion; statistical analysis; Dempster-Shafer theory; data fusion process; evidential reasoning; fuzzy statistical approach; mass functions assignment; remote sensing data fusion; simulated noisy fuzzy image; Algorithm design and analysis; Bayesian methods; Data analysis; Fuzzy reasoning; Instrumentation and measurement; Remote sensing; Statistical analysis; Stochastic processes; Testing; Uncertainty; Dempster-Shafer theory; Evidential reasoning; data fusion; fuzzy statistical analysis;
         
        
        
        
            Conference_Titel : 
Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008. IEEE
         
        
            Conference_Location : 
Victoria, BC
         
        
        
            Print_ISBN : 
978-1-4244-1540-3
         
        
            Electronic_ISBN : 
1091-5281
         
        
        
            DOI : 
10.1109/IMTC.2008.4547151