Mutispectral image fusion for target detection

Marom Leviner; Masha Maltz

doi:10.1117/12.831330

23 September 2009 Multispectral image fusion for target detection

Marom Leviner, Masha Maltz

Proceedings Volume 7481, Electro-Optical and Infrared Systems: Technology and Applications VI; 748116 (2009) https://doi.org/10.1117/12.831330
Event: SPIE Security + Defence, 2009, Berlin, Germany

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.

Citation Download Citation

Marom Leviner and Masha Maltz "Multispectral image fusion for target detection", Proc. SPIE 7481, Electro-Optical and Infrared Systems: Technology and Applications VI, 748116 (23 September 2009); https://doi.org/10.1117/12.831330

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