By Topic

Comparison of several fusion paradigms applied to pixel-based image classification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Francois Leduc ; Defence R&D Canada ¿ Valcartier, 2459 Boul. Pie-XI Nord, Val-Bélair, QC, G3J 1X5, Canada. francois.leduc@drdc-rddc.gc.ca

This paper is concerned with the development of FuRII, a pixel-based image classification tool developed at DRDC Valcartier. FuRII is based on fuzzy sets and evidence theories and is implemented as an ENVI toolbox. The aim with this tool is to compare several fusion operators and rules in the context of image classification applied to land cover mapping. Several fuzzy fusion operators (conjunctive, disjunctive, adaptive and quantified adaptive fusion) and evidential fusion rules (Dempster, Dubois and Prade, Yager and Smets) are tested. FuRII permits to model imprecise knowledge with membership functions and fusion can be performed directly with membership values or with mass functions. In this later case, a transformation of membership values into basic belief values is computed. Finally, FuRII permits integration of source reliability into the fusion process

Published in:

2006 9th International Conference on Information Fusion

Date of Conference:

10-13 July 2006