We present a new approach to hyperspectral imaging that is inspired by biological imaging systems, such as human vision, which employ high spectral-and spatial discrimination only in a small central patch. This foveal technique addresses several problems of conventional approaches to HSI: they cannot provide snapshot, high spectral-resolution imagery in a two dimensional format. The ability to provide the data in a single snapshot removes temporal misregistration issues. High signal to noise ratios naturally result from the absence of any multiplexing technique and the corresponding loss of light. Other reported snapshot techniques are either low spectral resolution or provide only a one-dimensional field of view. A high-spectral-resolution imager with a wide field of view could produce giga-sample data rates, which would make real-time data processing problematic. By gathering hyperspectral data from only a selected portion of the scene, we reduce the data processing rates to manageable levels. For many applications only a small field of view is required, but needs to be cued for situational awareness. In our system, this is provided for by a wide field of view, panchromatic imager, which fills a similar role to peripheral vision in the biological systems mentioned above. Our technique images the selected region onto a coherent fibre bundle, which reformats the input into a line array constituting the input to a dispersive hyperspectral imager. Computer processing reformats the dispersed one-dimensional output into a rectangular image and applies calibration routines to produce a high spectral resolution, small hyperspectral image. This is combined with a high-spatial-resolution panchromatic image. Experimental results will be presented.
