Image distortion calibration of imaging spectrometer with grating by SVM

Imaging spectrometer was a kind of optical remote sensing instruments which combined image with spectrum. Grating imaging spectrometer can acquire data cube. When the sampling frequency and splicing was reasonable, because of the nonlinear about dispersive elements making spectral expansion, lead to the distortion of strip image, as well as the distortion of spliced image. The distortion feature points were extracted more accurate by using the gray gradient from the edge to the center and genetic algorithm. By choosing appropriate parameters, we established the support vector machine regression mathematical model to correct the distortion. Compared with the conventional distortion correction method. This method was able to balance effectively the error from the global and the local and improve the accuracy of correction. The calibration of error can be controlled within 0.5 pixels by experimental verification.