An out-of-focus blur removal technique for high-throughput overlay measurement

As semiconductor microfabrication technology advances and manufacturing processes become more complex, Critical Dimension-Scanning Electron Microscope (CD-SEM) which plays a crucial role in high-precision process control has become increasingly important. Especially, there is a constant demand for improving the throughput of CD-SEM while maintaining high measurement accuracy. Therefore, we propose a new out-of-focus blur removal technique based on deep learning (DL) for OVL measurement, that can transform blurred low-dose SEM images, captured under high-throughput conditions, into sharp high-dose SEM images with high measurement accuracy to improve the throughput of CD-SEM. It reduces not only image capturing time but also focus adjustment time. To verify the effectiveness of the proposed solution, we evaluated it in terms of image quality and OVL measurement accuracy. The experimental results demonstrated that it successfully reduces both blur and noise while maintaining high measurement accuracy.