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New Poisson denoising method for pulse-count STEM imaging.

Taichi Kusumi¹, Shun Katakami¹, Ryo Ishikawa²

¹Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha 5-1-5, Chiba 277-8561, Kashiwa, Japan.

Ultramicroscopy

|June 17, 2024

Summary

This summary is machine-generated.

We developed a Poisson denoising method for electron counting imaging in scanning transmission electron microscopy. This method significantly reduces electron dose while improving image quality for atomic-resolution studies.

Keywords:

Bayesian inference Markov random field model Poisson denoising Pulse count Scanning transmission electron microscopy

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Area of Science:

Materials Science
Physics
Imaging Science

Background:

Advancements in electron microscopy detectors enable direct electron counting per pixel.
Electron counting imaging offers potential for higher resolution and reduced sample damage.
Optimizing denoising is crucial for extracting meaningful data from low-dose electron counting images.

Purpose of the Study:

To develop and optimize a denoising method specifically for atomic-resolution scanning transmission electron microscopy (STEM) electron counting images.
To enable significant reduction in electron dose while maintaining or improving image quality.
To compare reconstruction methods for denoised electron counting images.

Main Methods:

Proposed a Poisson denoising method based on Markov random field models and Bayesian inference.
Applied the method to atomic-resolution scanning transmission electron microscopy images.
Investigated reconstruction from multiple non-integrated images versus integrated images.

Main Results:

The proposed Poisson denoising method effectively reduces noise in electron counting images.
Achieved significant electron dose reduction, by a factor of approximately 15 times or more.
Reconstruction from multiple, non-integrated images yielded superior results compared to using a single integrated image.

Conclusions:

The developed Poisson denoising method is effective for low-dose, atomic-resolution STEM electron counting imaging.
Significant dose reduction is achievable, preserving structural information.
Multi-image reconstruction without integration is a more effective strategy for this type of imaging.