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

Savitzky, Benjamin H.; El Baggari, Ismail; Clement, Colin B.; Waite, Emily; Goodge, Berit H.; Baek, David J.; Sheckelton, John P.; Pasco, Christopher; Nair, Hari; Schreiber, Nathaniel J.; Hoffman, Jason; Admasu, Alemayehu S.; Kim, Jaewook; Cheong, Sang -Wook; Bhattacharya, Anand; Schlom, Darrell G.; McQueen, Tyrel M.; Hovden, Robert; Kourkoutis, Lena F.

doi:10.1016/j.ultramic.2018.04.008

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

Journal Article · Fri Apr 27 00:00:00 EDT 2018 · Ultramicroscopy

DOI:https://doi.org/10.1016/j.ultramic.2018.04.008· OSTI ID:1479486

Savitzky, Benjamin H. ^[1]; El Baggari, Ismail ^[1]; Clement, Colin B. ^[1]; Waite, Emily ^[1]; ^[1]; Baek, David J. ^[1]; Sheckelton, John P. ^[2]; ^[2]; Nair, Hari ^[1]; Schreiber, Nathaniel J. ^[1]; Hoffman, Jason ^[3]; Admasu, Alemayehu S. ^[4]; Kim, Jaewook ^[4]; Cheong, Sang -Wook ^[4]; Bhattacharya, Anand ^[5]; Schlom, Darrell G. ^[1]; McQueen, Tyrel M. ^[2]; Hovden, Robert ^[6]; Kourkoutis, Lena F. ^[1]

Cornell Univ., Ithaca, NY (United States)
The Johns Hopkins Univ., Baltimore, MD (United States)
Argonne National Lab. (ANL), Argonne, IL (United States); Harvard Univ., Cambridge, MA (United States)
Rutgers Univ., Piscataway, NJ (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)
Cornell Univ., Ithaca, NY (United States); Univ. of Michigan, Ann Arbor, MI (United States)

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 liq- uid 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 identi cation of incorrect image registrations, and determination of the optimal image shifts from the complete set of relative shifts. Here, 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 Å are achieved at 300 kV and with the sample cooled to near liquid nitrogen temperature.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Lab. (ANL), Argonne, IL (United States)

Sponsoring Organization:: Air Force Research Laboratory (AFRL), Air Force Office of Scientific Research (AFOSR); Gordon and Betty Moore Foundation; National Science Foundation (NSF); USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Materials Sciences & Engineering Division

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1479486

Alternate ID(s):: OSTI ID: 1703388
OSTI ID: 22807867

Journal Information:: Ultramicroscopy, Journal Name: Ultramicroscopy Journal Issue: C Vol. 191; ISSN 0304-3991

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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47 OTHER INSTRUMENTATION
Atomic Resolution
Cryogenic STEM (cryo-STEM)
Image reconstruction
Low signal-to-noise ratio (SNR)
Rigid registration
Scanning Transmission Electron Microscopy (STEM)

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

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