Methods for image simulation, pseudo-random defect dataset generation, and micro and nano defects detection

Abstract

The embodiments of the present disclosure provide a method for an image simulation generation based on a near-field simulation of a computational electromagnetic field, the method comprising: constructing a simulated three-dimensional model based on model parameters; constructing a simulated Kohler illumination model based on a light source parameter; using a degree of similarity change in a synthesized image under incremental aperture diaphragm sampling points as a criterion for approximate convergence of the simulation to determine a count of samples to be used for a balancing combination of simulation cost and accuracy; an optical simulation is performed based on the simulated three-dimensional model and the simulated Kohler illumination model, and a far-field electromagnetic field distribution data is obtained to obtain a simulated image by synthesizing the image. In the generation of a large count of simulated images on the basis of pseudo-random defect dataset generation may be further realized, in the acquisition of a large count of datasets, the dataset of defect inspection model may be trained, in order to achieve a direct detection for patterned wafer defective images and solve the problem of difficult access to reference images in a process of patterned wafer defect detection.