Accuracy improvement of phase estimation in electron holography using noise reduction methods

We try to improve the limit of the phase estimation of the interference fringe at low electron dose levels in electron holography by a noise reduction method. In this paper, we focus on unsupervised approaches to apply it to electron beam-sensitive and unknown samples and describe an overview of denoising methods used widely in image processing, such as wiener filter, total variation denoising, nonlocal mean filters and wavelet thresholding. We compare the wavelet hidden Markov model (WHMM) denoising that we have studied so far with the other conventional noise reduction methods. We evaluate the denoise performance of each method using the peak signal-to-noise ratio between noise-free and the target holograms (noisy or denoised holograms) and the root mean-square error (RMSE) between the true phase of the fringe and the measured phase by the discrete Fourier transform phase estimator. We show the denoised holograms for simulation and experimental data by using each noise reduction method and then discuss evaluation indexes obtained from these denoised holograms. From experimental results, it can be seen that the WHMM denoising can reduce the RMSE of fringe phase to about 1/4.5 for noisy simulation holograms and it has stable and good performance for noise reduction of observed holograms with various image qualities.