By Topic

A new image fusion algorithm based on wavelet packet analysis and PCNN

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

2 Author(s)
Wei Li ; Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China ; Xue-Feng Zhu

In this paper, a new image fusion algorithm based on wavelet packet analysis (WPA) and pulse-coupled neural networks (PCNN) is presented. Firstly a multi-scale decomposition of each source image is performed by wavelet packet transform (WPT), and then the PCNN is used to make an intelligent fusion decision to obtain the fusion coefficients in all wavelet packet fields. Finally an inverse WPT based on the new fused coefficients is taken to reconstruct fusion image. The highlight of the new algorithm is to utilize the global feature of source images because the PCNN has the global couple and pulse synchronization characteristics. It accords with the physiological characteristic of human visual neural system. Series of experiments are performed on comparing the new algorithm with some other existing fusion methods. The experimental results show that the new algorithm is very effective and provides a better performance in fusing multi-source images.

Published in:

2005 International Conference on Machine Learning and Cybernetics  (Volume:9 )

Date of Conference:

18-21 Aug. 2005