How should a fixed budget of dwell time be spent in scanning electron microscopy to optimize image quality?

TL;DR

This paper compares three algorithm-assisted scanning strategies in electron microscopy under fixed dwell time constraints, finding sparse scanning with inpainting outperforms denoising and super-resolution methods.

Contribution

It introduces a comparative evaluation of different image acquisition strategies in SEM, highlighting the effectiveness of sparse scanning with inpainting.

Findings

Sparse scanning with inpainting outperforms denoising and super-resolution methods.

Increased beam currents improve image quality across strategies.

Optimal dwell time allocation depends on the chosen reconstruction technique.

Abstract

In scanning electron microscopy, the achievable image quality is often limited by a maximum feasible acquisition time per dataset. Particularly with regard to three-dimensional or large field-of-view imaging, a compromise must be found between a high amount of shot noise, which leads to a low signal-to-noise ratio, and excessive acquisition times. Assuming a fixed acquisition time per frame, we compared three different strategies for algorithm-assisted image acquisition in scanning electron microscopy. We evaluated (1) raster scanning with a reduced dwell time per pixel followed by a state-of-the-art Denoising algorithm, (2) raster scanning with a decreased resolution in conjunction with a state-of-the-art Super Resolution algorithm, and (3) a sparse scanning approach where a fixed percentage of pixels is visited by the beam in combination with state-of-the-art inpainting algorithms. Additionally, we considered increased beam currents for each of the strategies. The experiments showed that sparse scanning using an appropriate reconstruction technique was superior to the other strategies.