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Proceedings Paper

Mutispectral image fusion for target detection
Author(s): Marom Leviner; Masha Maltz
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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)

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