In this study, a noise-reduction technique for series low-dose electron holograms using tensor decomposition is demonstrated through simulation. We treated an entire dataset of the series holograms with Poisson noise as a third-order tensor, which is a stack of two-dimensional holograms. The third-order tensor, which is decomposed into a core tensor and three factor matrices, is approximated as a lower-rank tensor using only noise-free principal components. This technique is applied to simulated holograms by assuming a p-n junction in a semiconductor sample. The peak signal-to-noise ratios of the holograms and the reconstructed phase maps have been improved significantly using tensor decomposition. Moreover, the proposed method was applied to a more practical situation of time-resolved in situ electron holography by considering a non-uniform fringe contrast and fringe drift relative to the sample. The accuracy and precision of the reconstructed phase maps were quantitatively evaluated to demonstrate its effectiveness for in situ experiments and low-dose experiments on beam-sensitive materials.

中文翻译：

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使用张量分解对系列电子全息图进行去噪

在这项研究中，通过模拟展示了使用张量分解的系列低剂量电子全息图降噪技术。我们将具有泊松噪声的系列全息图的整个数据集视为三阶张量，它是二维全息图的堆栈。三阶张量分解为核心张量和三个因子矩阵，仅使用无噪声主成分近似为低阶张量。通过假设半导体样品中存在 pn 结，该技术可应用于模拟全息图。全息图的峰值信噪比和重建的相位图使用张量分解得到了显着改善。而且，通过考虑非均匀条纹对比度和相对于样品的条纹漂移，将所提出的方法应用于时间分辨原位电子全息的更实际情况。对重建的相位图的准确性和精度进行了定量评估，以证明其对光束敏感材料的原位实验和低剂量实验的有效性。