Pattern selection in high-dimensional parameter spaces

Pattern selection for OPC model calibration is frequently done by image parameter space (IPS) coverage methods. There ensure that the images of the chosen test patterns cover important regions of an n-dimensional parameter space spawned by image parameters, such as minimum and maximum intensity I-min, I-max, curvature, slope and image density. But such a small number of parameteres is often insufficient for finding ensures coverage of a high dimensional parameter space with a high number of parameters, even permitting the use of all pixels of the aerial images (n >> 1000) as parameters.