Accelerating computed tomographic imaging spectrometer reconstruction using a parallel algorithm exploiting spatial shift-invariance

TL;DR

This paper introduces a highly parallelizable algorithm for CTIS image reconstruction that exploits spatial shift-invariance, enabling real-time hyperspectral imaging with implementations on desktop and embedded GPUs, achieving unprecedented speed.

Contribution

The paper presents a novel parallel algorithm exploiting spatial shift-invariance for CTIS reconstruction, with implementations on desktop and embedded GPUs, achieving the fastest times reported.

Findings

Achieved the fastest CTIS reconstruction times to date.

Developed GPU-based implementations for real-time processing.

Demonstrated algorithm versatility on different hardware platforms.

Abstract

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