Share Email Print
cover

Proceedings Paper

Mutispectral image fusion for target detection
Author(s): Marom Leviner; Masha Maltz
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Paper Details

Date Published: 23 September 2009
PDF: 6 pages
Proc. SPIE 7481, Electro-Optical and Infrared Systems: Technology and Applications VI, 748116 (23 September 2009); doi: 10.1117/12.831330
Show Author Affiliations
Marom Leviner, Ben-Gurion Univ. of the Negev (Israel)
Masha Maltz, Ben-Gurion Univ. of the Negev (Israel)


Published in SPIE Proceedings Vol. 7481:
Electro-Optical and Infrared Systems: Technology and Applications VI
David A. Huckridge; Reinhard R. Ebert, Editor(s)

© SPIE. Terms of Use
Back to Top