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23 September 2009 Multispectral image fusion for target detection
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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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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