Chromotomography is a form of hyperspectral imaging that uses a prism to simultaneously record spectral and spatial information, like a slitless spectrometer. The prism is rotated to provide multiple projections of the 3D data cube on the 2D detector array. Tomographic reconstruction methods are then used to estimate the hyperspectral data cube from the projections. This type of system can collect hyperspectral imagery from fast transient events, but suffers from reconstruction artifacts due to the limited-angle problem. Several algorithms have been proposed in the literature to improve reconstruction, including filtered backprojection, projection onto convex sets, subspace constraint, and split- Bregman iteration. Here we present the first direct comparison of multiple methods against a variety of simulatedtargets. Results are compared based on both image quality and spectral accuracy of the reconstruction, where previous literature has emphasized imaging only. In addition, new algorithms and HSI quality metrics are proposed. We find the quality of the results depend strongly on the spatial and spectral content of the scene, and no single algorithm is consistently superior over a broad range of scenes.
Chromotomography is a form of hyperspectral imaging that utilizes a spinning diffractive element to resolve a rapidly
evolving scene. The system captures both spatial dimensions and the spectral dimension at the same time. Advanced
algorithms take the recorded dispersed images and use them to construct the data cube in which each reconstructed
image is the recorded scene at a specific wavelength. A simulation tool has been developed which uses Zemax to
accurately trace rays through real or proposed optical systems. The simulation is used here to explore the limitations of
tomographic reconstruction in both idealized and aberrated imaging systems. Results of the study show the accuracy of
reconstructed images depends upon the content of the original target scene, the number of projections measured, and the
angle through which the prism is rotated. For cases studied here, 20 projections are sufficient to achieve image quality
99.51% of the max value. Reconstructed image quality degrades with aberrations, but no worse than equivalent
A fieldable hyperspectral chromotomographic imager has been developed at the Air Force Institute of Technology to refine component requirements for a space-based system. The imager uses a high speed visible band camera behind a direct-vision prism to simultaneously record two spatial dimensions and the spectral dimension. Capturing all three dimensions simultaneously allows for the hyperspectral imaging of transient events. The prism multiplexes the spectral and spatial information, so a tomographic reconstruction algorithm is required to separate hyperspectral channels. The fixed dispersion of the prism limits the available projections, leading to artifacts in the reconstruction which limit the image quality and spectrometric accuracy of the reconstructions. The amount of degradation is highly dependent on the content of the scene. Experiments were conducted to characterize the image and spectral quality as a function of spatial, spectral, and temporal complexity. We find that in general, image quality degrades as the source bandwidth increases. Spectra estimated from the reconstructed data cube are generally best for point-like sources, and can be highly inaccurate for extended scenes. In other words, the spatial accuracy varies inversely with the spectral width, and the spectral accuracy varies inversely with the spatial width. Experiment results also demonstrate the ability to reconstruct hyperspectral images from transient combustion events.