Abstract
In this paper, we present a novel multimodal image fusion algorithm in the independent component analysis (ICA) domain. Region-based fusion of ICA coefficients is implemented, where segmentation is performed in the spatial domain and ICA coefficients from separate regions are fused separately. The ICA coefficients from given regions are consequently weighted using the Piella fusion metric in order to maximize the quality of the fused image. The proposed method exhibits significantly higher performance than the basic ICA algorithm and also shows improvement over other state-of-the-art algorithms
| Translated title of the contribution | Region-based multimodal image fusion using ICA bases |
|---|---|
| Original language | English |
| Pages (from-to) | 743 - 751 |
| Number of pages | 9 |
| Journal | IEEE Sensors Journal |
| Volume | 7 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - May 2007 |
Bibliographical note
Publisher: Institute of Electrical and Electronics EngineersRose publication type: Journal article
Sponsorship: This work was supported in part by the U.K. Ministry of Defence
Data and Information Fusion Defence Technology Centre.
Terms of use: Copyright © 2007 IEEE. Reprinted from IEEE Sensors Journal.
This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected].
By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Keywords
- fusion metrics
- image fusion
- independent component analysis (ICA)
- region-based fusion