Major spin-offs from NASA's multi- and hyperspectral imaging remote sensing technology developed for Earth resources monitoring, are creative techniques that combine and integrate spectral with spatial methods. Such techniques are finding use in medicine, agriculture, manufacturing, forensics, and an ever expanding list of other applications. Many such applications are easier to implement using a sensor design different from the pushbroom or whiskbroom air- or space-borne counterparts. This need is met by using a variety of electronically tunable filters that are mounted in front of a monochrome camera to produce a stack of images at a sequence of wavelengths, forming the familiar "image cube". The combined spectral/spatial analysis offered by such image cubes takes advantage of tools borrowed from spatial image processing, chemometrics and specifically spectroscopy, and new custom exploitation tools developed specifically for these applications. Imaging spectroscopy is particularly useful for non homogeneous samples or scenes. Examples include spatial classification based on spectral signatures, use of spectral libraries for material identification, mixture composition analysis, plume detection, etc. This paper reviews available tunable filters, system design considerations, general analysis techniques for retrieving the intrinsic scene properties from the measurements, and applications and examples.
