Defect detection in patterned wafers using multichannel Scanning Electron Microscope

Recent computational methods of wafer defect detection often inspect Scanning Electron Microscope (SEM) images of the wafer. In this paper, we propose a kernel-based approach to multichannel defect detection, which relies on simultaneous acquisition of three different images for each sample in an SEM tool. The reconstruction of a source patch from reference patches in the three channels is constrained by a similarity criterion across the three SEM images. The improved performance of the proposed algorithm is demonstrated, compared to a single-channel kernel-based defect detection method.