Redundant Cross-Correlation for Drift Correction in SEM Nanoparticle Imaging

TL;DR

This paper introduces a novel post-processing algorithm using redundant cross-correlation to correct drift in SEM nanoparticle images, significantly improving image quality without hardware modifications.

Contribution

The paper presents a new algorithm that combines multiple noisy SEM images to correct drift and enhance image quality, preserving geometrical features.

Findings

Mean SNR increased from 4.4 dB to 11.3 dB with five images

Method preserves geometrical properties and surface features

Effective in nanoparticle imaging without hardware drift correction

Abstract

Scanning Electron Microscopy (SEM) is a widely used tool for nanoparticle characterization, but long-term directional drift can compromise image quality. We present a novel algorithm for post-imaging drift correction in SEM nanoparticle imaging. Our approach combines multiple rapidly acquired, noisy images to produce a single high-quality overlay through redundant cross-correlation, preventing drift-induced distortions. The preservation of critical geometrical properties and accurate imaging of surface features were verified using Atomic Force Microscopy. On platinum nanoparticles with diameters of 300 to 1000 nm, significant improvements in the mean-based signal-to-noise ratio (SNR) were achieved, increasing from 4.4 dB in single images to 11.3 dB when overlaying five images. This method offers a valuable tool for enhancing SEM image quality in nanoparticle research and metrology, particularly in settings without specialized hardware-based drift correction.