The hyperspectral imaging trade-off

Although it has no clear-cut definition, hyperspectral imaging in the UV-Visible-NIR wavelength region seems to mean spectral image sampling in bands from 10 nm width or narrower that enables spectral reconstruction over some wavelength interval. For non-imaging spectral applications, this will be the standard situation, and it enables the detection of small spectral features like peaks, valleys and shoulders for a wide range of chemistries. Everything else being equal this is what you would wish for, and hyperspectral imaging is often used in research and in remote sensing because of the needs and cost structures in these projects. However, hyperspectral imaging is a sampling choice within spectral imaging that typically will impose some trade-offs, and these trade-offs will not be optimal for many applications. The purpose of this presentation is to point out and increase the awareness of these trade-offs to provide a requirement-balanced sampling choice for close-range spectral imaging applications. In close-range imaging we have more degrees of freedom in the design of a spectral imaging system e.g. in terms of sample preparation, sample presentation, illumination, image acquisition, and control. The choice of spectral imaging system will influence many system parameters like 1. Spectral resolution 2. Spatial resolution 3. Time of acquisition and processing 4. Flexibility of acquisition and processing 5. Spectral dynami c range 6. Feasibility of high dynamic range (HDR) imaging 7. Need for movement during acquisition 8. System price Spectral resolution has an obvious interest, but it is the experience of the author, that the vast majority of real spectral imaging applications only need to unmix 2-5 different components. This should be possible with a sensible choice of 10-20 wavelengths. This presentation will show how spectral resolution in these situations can be traded off with improvements in the parameters above.