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

fYear

2008

fDate

12-15 May 2008

Firstpage

825

Lastpage

829

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008. IEEE

Conference_Location

Victoria, BC

ISSN

1091-5281

Print_ISBN

978-1-4244-1540-3

Electronic_ISBN

1091-5281

Type

conf

DOI

10.1109/IMTC.2008.4547151

Filename

4547151