Spectral image reconstruction of coded aperture spectral imaging system based on compressed sensing

Aiming at the current status that the reconstruction quality of spectral image is yet to be enhanced, an improved two-step iterative shrinkage/threshold (TwIST) algorithm is proposed in this paper. Firstly, according to the coded aperture spectral imaging principle, a mathematical model for spectral image reconstruction of coded aperture spectral imaging system based on compressed sensing is established. Then, taking the spatial smooth transition characteristics of spectral image as a priori knowledge, two improvements are proposed based on the traditional TwIST algorithm, selecting the total variation regular constraint terms and denoising the updated terms in each iteration. Finally, in order to verify the improved algorithm, the reconstructed spectral images are simulated. It shows the reconstructed spectral images retain the spatial details well, and the reconstructed spectral curve is in good agreement with the original spectral curve, indicating that the improved algorithm is effective in the high-precision reconstruction of spatial information and spectral information of the target.