In Computational Spectral imaging, two-dimensional coded apertures and dispersive elements realize the mixed modulation of spatial information and spectral information of the target respectively, and then reconstruct the threedimensional data cube. Therefore, coded aperture plays a vital role. In the imaging process, by moving the coded aperture to increase the number of measurements, the aperture moved one code element at each step to simulate the actual 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 were analyzed. The Least Square (LS) algorithm was considered to reconstruct three-dimensional data cube. Compared with the classical Two-step Iterative Shrinkage/Thresholding (TwIST) algorithm, the reconstructed Structural Similarity Index Measurement (SSIM) and Peak Signal to Noise Ratio (PSNR) by LS algorithm were better than TwIST algorithm. It was indicated that the SSIM and PSNR increased with the increasing number of measurements. When the number of measurements was similar with the number of spectral segments, the SSIM of the three coded apertures reached more than 0.9 by LS algorithm. However, the SSIM and PSNR of the Gauss random coded aperture were the largest Obviously, which are 0.995 and 52.560, respectively. And the PSNR of Gauss random coded aperture was 13 dB more than that of Hadamard and Harmonic coded apertures. When the number of measurements was constant, the SSIM and PSNR decrease gradually with the increasing number of spectral segments. The simulation results showed that the LS algorithm was superior to the TwIST algorithm in the reconstruction process, and the Gauss random coded aperture had the best performance.