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Accuracy improvement of phase estimation in electron holography using noise reduction methods
Yoshihiro Midoh1, Koji Nakamae1
1Department of Information Systems Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Microscopy (Oxford, England)
|January 25, 2020
Summary
We developed a noise reduction method for electron holography to improve phase estimation at low electron doses. The wavelet hidden Markov model (WHMM) denoising significantly reduces phase errors, enhancing image quality for sensitive samples.
Area of Science:
- Electron microscopy
- Holography
- Image processing
Background:
- Electron holography is crucial for analyzing beam-sensitive samples.
- Accurate phase estimation is limited by noise at low electron doses.
- Unsupervised denoising methods are needed for unknown samples.
Purpose of the Study:
- To enhance phase estimation accuracy in electron holography at low electron doses.
- To evaluate and compare various unsupervised noise reduction techniques.
- To introduce and assess the performance of Wavelet Hidden Markov Model (WHMM) denoising.
Main Methods:
- Overview of denoising methods: Wiener filter, Total Variation, Nonlocal Means, Wavelet Thresholding.
- Implementation and comparison of Wavelet Hidden Markov Model (WHMM) denoising.
- Performance evaluation using Peak Signal-to-Noise Ratio (PSNR) and Root Mean Square Error (RMSE).
Main Results:
- WHMM denoising demonstrated superior performance compared to conventional methods.
- RMSE of fringe phase was reduced by approximately 1/4.5 for noisy simulation holograms.
- Stable and effective noise reduction was observed across holograms of varying image quality.
Conclusions:
- WHMM denoising offers a robust solution for improving phase estimation in low-dose electron holography.
- The method is suitable for electron beam-sensitive and unknown samples.
- This technique enhances the reliability and quality of electron holography data.
