Modeling and Optimization of Image Mapper for Snapshot Image Mapping Spectrometer

Image mapping spectrometer (IMS) is a hyperspectral imager that can obtain the spatial and spectral information of an object simultaneously in real time. The cross talk on the pupil array plane results in degradation of the final image contrast, the reduction of the detector dynamic range, and the aliasing of the spatial–spectral information. This paper presents a novel approach to designing an image mapper that can be used in IMS to reduce cross talk between adjacent sub-pupils. To verify the proposed method, an imaging model based on scalar diffraction theory is derived and computer simulations are conducted to evaluate the improvement that is realized compared with the original method. In addition, image mappers designed by both the proposed approach and the original approach are fabricated. The simulation and experimental results show that there is a reduction of about 30%–70% in the cross talk obtained using the novel image mapper, which proves that the proposed approach is effective and has advantages in improving the data quality of the IMS.