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Spectral imaging enables the analysis of optical material properties that areinvisible to the human eye. Different spectral capturing setups, e.g., based onfilter-wheel, push-broom, line-scanning, or mosaic cameras, have beenintroduced in the last years to support a wide range of applications inagriculture, medicine, and industrial surveillance. However, these systemsoften suffer from different disadvantages, such as lack of real-timecapability, limited spectral coverage or low spatial resolution. To addressthese drawbacks, we present a novel approach combining two calibratedmultispectral real-time capable snapshot cameras, covering different spectralranges, into a stereo-system. Therefore, a hyperspectral data-cube can becontinuously captured. The combined use of different multispectral snapshotcameras enables both 3D reconstruction and spectral analysis. Both capturedimages are demosaicked avoiding spatial resolution loss. We fuse the spectraldata from one camera into the other to receive a spatially and spectrally highresolution video stream. Experiments demonstrate the feasibility of thisapproach and the system is investigated with regard to its applicability forsurgical assistance monitoring.

Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene Reconstruction