  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.
