Image registration of low signal-to-noise cryo-STEM data

TL;DR

This paper introduces a novel image registration method for low-SNR cryo-STEM data that improves alignment accuracy and artifact reduction, enabling high-resolution atomic imaging at cryogenic temperatures.

Contribution

The authors develop a new registration approach that leverages all pairwise image comparisons and physical stage drift models to enhance low-SNR image stack alignment.

Findings

Effective registration of challenging low-SNR cryo-STEM images.

High-resolution averages with 0.72 Å detail achieved.

Reduction of artifacts endemic to low-SNR lattice images.

Abstract

Combining multiple fast image acquisitions to mitigate scan noise and drift artifacts has proven essential for picometer precision, quantitative analysis of atomic resolution scanning transmission electron microscopy (STEM) data. For very low signal-to-noise ratio (SNR) image stacks - frequently required for undistorted imaging at liquid nitrogen temperatures - image registration is particularly delicate, and standard approaches may either fail, or produce subtly specious reconstructed lattice images. We present an approach which effectively registers and averages image stacks which are challenging due to their low-SNR and propensity for unit cell misalignments. Registering all possible image pairs in a multi-image stack leads to significant information surplus. In combination with a simple physical picture of stage drift, this enables identification of incorrect image registrations, and determination of the optimal image shifts from the complete set of relative shifts. We demonstrate the effectiveness of our approach on experimental, cryogenic STEM datasets, highlighting subtle artifacts endemic to low-SNR lattice images and how they can be avoided. High-SNR average images with information transfer out to 0.72 A are achieved at 300 kV and with the sample cooled to near liquid nitrogen temperature.