Computational Reconfigurable Imaging Spectrometer (CRISP)

Hyperspectral imaging spectrometers are incredibly useful in diverse fields such as environmental monitoring, biomedical imaging, hazard detection, agriculture, and mineralogy. However, their extensive utilization is disrupted by exorbitantly high cost and complexity that primarily stem from the large, expensive components required. Current hyperspectral imaging technology generally needs robust, expensive components to function effectively, resulting in size and weight constraints that restrict their use in space or airborne applications. Furthermore, these devices typically have high power requirements, making them unfeasible for small platforms. Practically, these requirements have restricted the deployment of these spectrometers in situations where small, portable devices are favored.

Technology Description

Reconfigurable hyperspectral imaging spectrometers are technological devices that show great promise in areas like environmental monitoring, biomedical imaging, hazard detection, agriculture, and mineralogy. The key feature lies in its employment of computational imaging techniques, which enable these spectrometers to achieve high performance with less expensive, smaller, and noisier components, including uncooled microbolometers. Spectrally coded focal-plane masks and platform motion are used to modulate the optical spectrum, which subsequently allows simultaneous measurement of multiple spectral bins. Demodulation of this coded pattern returns an optical spectrum at each pixel. What distinguishes this technology from conventional hyperspectral imagers is its potential for lower cost and complexity, addressing long-standing challenges in fielding spaceborne hyperspectral imagers. The computational reconfigurable design enables these imagers to conform to the stipulations of small space and air platforms, which have stringent size, weight, and power constraints. This makes them desirable for applications that require compact or less expensive packaging.