Error analysis and reconstruction for diffractive optic imaging spectrometer using the multiple iterations

Diffraction imaging spectrometer cannot acquire imaging spectral data without calculation and inversion. In this paper, the imaging process of the diffraction imaging spectrometer and the principle of the data error from both space and spectra are analyzed. To solve the problems of low definition of the reconstruction and the ringing in it occurring under the condition that the point spread function (PSF) is larger, a new algorithm is proposed based on improved inverse Wiener filtering. The improved method regards the reconstruction result of Wiener filtering as a new fuzzy image, and recalculates the PSF of the new fuzzy image based on the analysis of the diffraction characteristics and error. Inverse iterative Wiener filtering is used to improve the definition of the reconstruction, and then the noise needs to be removed according to the distribution of the spatial and spectral features. Simulated diffraction imaging spectral data are used to verify the correctness of the algorithm proposed in this paper. A reconstruction without ringing can be obtained when the standard deviation of PSF is 2.5, and both of the definition and detail ability are higher than those of the traditional reconstruction. The reconstruction using the improved algorithm proposed in this paper can satisfy the applications of the diffraction imaging spectral data.