Computed tomographic imaging spectrometers capture hyperspectral images in realtime. However, postprocessing the imagery can require enormous computational resources; thus, limiting its application to nonrealtime scenarios. To overcome these challenges, we developed a highly parallelizable algorithm that exploits spatial shift-invariance. To demonstrate the versatility of our algorithm, we developed implementations on a desktop and an embedded graphics processing unit. To our knowledge, our results show the fastest image reconstruction times reported.
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