Multisensor Fusion with Hyperspectral Imaging Data: Detection and Classification

■ We present two examples that show how fusing data from hyperspectral imaging (HSI) sensors with data from other sensors can enhance overall detection and classification performance. The first example involves fusing HSI data with foliage-penetration synthetic aperture radar (FOPEN SAR) data; the second example involves fusing HSI data with high-resolution imaging (HRI) data. The fusion of HSI and SAR data exploits different phenomenology from the two different sensors. The fusion of HSI and HRI data combines their superior respective spectral and spatial information. Fusion of HSI and SAR data is accomplished at the feature level. HSI data provide background characterization and material identification; HSI-SAR fusion allows us to reduce false detections and confirm target detection in the SAR image. Fusion of HSI and HRI data is implemented at both data and feature levels, resulting in a combined spatial-spectral analysis that enhances target identification.