The snapshot image mapping spectrometer（IMS） has advantages such as high temporal resolution,high throughput,compact structure and simple reconstructed algorithm.In recent years,it has been utilized in biomedicine,remote sensing,etc.However,the system errors and various factors can cause cross talk,image degradation and spectral distortion in the system.In this research,a theoretical model is presented along with the point response function（PRF） for the IMS,and the influence of the mirror tilt angle error of the image mapper and the prism apex angle error are analyzed based on the model.The results indicate that the tilt angle error causes loss of light throughput and the prism apex angle error causes spectral mixing between adjacent sub-images.The light intensity on the image plane is reduced to 95%when the mirror tilt angle error is increased to ±100 ＂（≈ 0.028°）.The prism apex error should be controlled within the range of 0-36＂（0.01°）to ensure the designed number of spectral bands,and avoid spectral mixing between adjacent images.
A light field modulated imaging spectrometer （LFMIS） can acquire the spatial-spectral datacube of targets of interest or a scene in a single shot. The spectral information of a point target is imaged on the pixels covered by a microlens. The pixels receive spectral information from different spectral filters to the diffraction and misalignments of the optical components. In this paper, we present a linear spectral multiplexing model of the acquired target spectrum. A calibration method is proposed for calibrating the center wavelengths and bandwidths of channels of an LFMIS system based on the liner-variable filter （LVF） and for determining the spectral multiplexing matrix. In order to improve the accuracy of the restored spectral data, we introduce a reconstruction algorithm based on the total least square （TLS） approach. Simulation and experimental results confirm the performance of the spectrum reconstruction algorithm and validate the feasibility of the proposed calibrating scheme.
Li-Juan SuQiang-Qiang YanYan YuanShi-Feng WangYu-Jian Liu
