Exploitation performance and characterization of a prototype compressive sensing imaging spectrometer

Abstract

The coded aperture snapshot spectral imager (CASSI) systems are a class of imaging spectrometers that provide a first-generation implementation of compressive sensing themes to the domain of hyperspectral imaging. Via multiplexing of information from different spectral bands originating from different spatial locations, a CASSI system undersamples the three-dimensional spatial/spectral data cube of a scene. Reconstruction methods are then used to recover an estimate of the full data cube. Here we report on our characterization of a CASSI system’s performance in terms of post-reconstruction image quality and the suitability of using the resulting data cubes for typical hyperspectral data exploitation tasks (e.g., material detection, pixel classification). The data acquisition and reconstruction process does indeed introduce trade-offs in terms of achieved image quality and the introduction of spurious spectral correlations versus data acquisition speedup and the potential for reduced data volume. The reconstructed data cubes are of sufficient quality to perform reasonably accurate pixel classification. Potential avenues to improve upon the usefulness of CASSI systems for hyperspectral data acquisition and exploitation are suggested.