In Computational Spectral imaging, two-dimensional coded apertures and dispersive elements realize the mixedmodulation of spatial information and spectral information of the target respectively, and then reconstruct the threedimensionaldata cube. Therefore, coded aperture plays a vital role. In the imaging process, by moving the codedaperture to increase the number of measurements, the aperture moved one code element at each step to simulate theactual push-broom process. Three types of coded apertures were considered, which are Gauss random coded aperture,Hadamard coded aperture and Harmonic coded aperture, and the reconstruction effect of the three coded apertures wereanalyzed. The Least Square (LS) algorithm was considered to reconstruct three-dimensional data cube. Compared withthe classical Two-step Iterative Shrinkage/Thresholding (TwIST) algorithm, the reconstructed Structural Similarity IndexMeasurement (SSIM) and Peak Signal to Noise Ratio (PSNR) by LS algorithm were better than TwIST algorithm. It wasindicated that the SSIM and PSNR increased with the increasing number of measurements. When the number ofmeasurements was similar with the number of spectral segments, the SSIM of the three coded apertures reached morethan 0.9 by LS algorithm. However, the SSIM and PSNR of the Gauss random coded aperture were the largestObviously, which are 0.995 and 52.560, respectively. And the PSNR of Gauss random coded aperture was 13 dB morethan that of Hadamard and Harmonic coded apertures. When the number of measurements was constant, the SSIM andPSNR decrease gradually with the increasing number of spectral segments. The simulation results showed that the LSalgorithm was superior to the TwIST algorithm in the reconstruction process, and the Gauss random coded aperture hadthe best performance.
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