Advances in Modeling of Scanning Charged-Particle-Microscopy Images

TL;DR

This paper discusses advanced modeling techniques for artificial SEM and ion microscope images, highlighting software improvements and applications like image evaluation and drift correction.

Contribution

It introduces an improved, versatile artificial image generator software capable of simulating various samples and drift functions, enhancing image analysis methods.

Findings

The software can generate arbitrary samples and drift functions.

Demonstrated the effectiveness of drift-corrected image composition.

Enhanced the evaluation of imaging and metrological techniques.

Abstract

Modeling artificial scanning electron microscope (SEM) and scanning ion microscope images has recently become important. This is because of the need to provide repeatable images with a priori determined parameters. Modeled artificial images are highly useful in the evaluation of new imaging and metrological techniques, like image-sharpness calculation, or drift-corrected image composition (DCIC). Originally, the NIST-developed artificial image generator was designed only to produce the SEM images of gold-on-carbon resolution sample for image-sharpness evaluation. Since then, the new improved version of the software was written in C++ programming language and is in the Public Domain. The current version of the software can generate arbitrary samples, any drift function, and many other features. This work describes scanning in charged-particle microscopes, which is applied both in the artificial image generator and the DCIC technique. As an example, the performance of the DCIC technique is demonstrated.