Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene
  Reconstruction
Eric L. Wisotzky Jost Triller Anna Hilsmann Peter Eisert
Spectral imaging enables the analysis of optical material properties that are
invisible to the human eye. Different spectral capturing setups, e.g., based on
filter-wheel, push-broom, line-scanning, or mosaic cameras, have been
introduced in the last years to support a wide range of applications in
agriculture, medicine, and industrial surveillance. However, these systems
often suffer from different disadvantages, such as lack of real-time
capability, limited spectral coverage or low spatial resolution. To address
these drawbacks, we present a novel approach combining two calibrated
multispectral real-time capable snapshot cameras, covering different spectral
ranges, into a stereo-system. Therefore, a hyperspectral data-cube can be
continuously captured. The combined use of different multispectral snapshot
cameras enables both 3D reconstruction and spectral analysis. Both captured
images are demosaicked avoiding spatial resolution loss. We fuse the spectral
data from one camera into the other to receive a spatially and spectrally high
resolution video stream. Experiments demonstrate the feasibility of this
approach and the system is investigated with regard to its applicability for
surgical assistance monitoring.