Simulation of pseudo cross-correlation degraded by the hyperspectral imaging of satellite complex motion

The present paper proposed a spectral degradation theory based on the point spread matrix, which is developed from the simulation algorithm of degradation based on differential dynamic spectral imaging for moving imaging. According to the eight neighborhood mixing model, considering the varying movement with time of the satellite platform, the situation that different object pixel has different point spread matrix is corresponding to the concept of the pseudo cross-correlation theory. Thus, the pseudo cross-correlation degradation theory of moving spectral imaging is presented. In this method, the point spread matrix is constructed by the mean mixing ratio of eight neighborhoods, which can be calculated by the POS data on satellite using the differential imaging theory based on image motion matrix. When calculating the point spread matrix with the simulating POS data curve, we found out that the point spread matrix can be simplified according to the importance of mixing effect to reduce calculation. Then, the presentation and computing method of the pseudo cross-correlation degradation theory of moving spectral imaging is clearly articulated, and the result of degradation simulating and calculating is evaluated qualitatively and quantitatively from imaging dimension and spectral dimension respectively, and the similarity between the degradation image and the initial image is revealed using the SSIM parameter. The pseudo cross-correlation degradation theory of moving spectral imaging improves the existing problem of spectral imaging degradation based on the complex movement of satellite platform. The simulation results show that this kind of degradation theory is suitable for solving the problem of spectral imaging degradation based on the complex satellite platform movement completely.