Cart (Loading....) | Create Account
Close category search window
 

Image fusion performance metric based on mutual information and entropy driven quadtree decomposition

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
$31 $31
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

4 Author(s)
Hossny, M. ; Centre for Intell. Syst. Res., Deakin Univ., Melbourne, VIC, Australia ; Nahavandi, S. ; Creighton, D. ; Bhatti, A.

The mutual information (MI) measure has become a popular metric to assess image fusion performance. However, despite its publicity, it provides a questionable result that consistently favours additive fusion (averaging) over multi-scale decomposition (MSD) fusion algorithms. Presented is a localised variation of MI to assess image fusion performance while preserving the importance of local structural similarity. The presented metric has been validated with extensive tests on popular image fusion test cases.

Published in:

Electronics Letters  (Volume:46 ,  Issue: 18 )

Date of Publication:

September 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.