A multi-modal and multi-scale non-local means (M3S-NLM) method is proposed to extract atomically resolved spectroscopic maps from low signal-to-noise (SNR) datasets recorded with a transmission electron microscope. This method improves upon previously tested denoising techniques as it takes into account the correlation between the dark-field signal recorded simultaneously with the spectroscopic dataset without compromising on the spatial resolution. The M3S-NLM method was applied to electron energy dispersive X-ray and electron-energy-loss spectroscopy (EELS) datasets. We illustrate the retrieval of the atomic scale diffusion process in an Al1-xInxN alloy grown on GaN and the surface oxidation state of perovskite nanocatalysts. The improved SNR of the EELS dataset also allows the retrieval of atomically resolved oxidation maps considering the fine structure absorption edge of LaMnO3 nanoparticles.

中文翻译：

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分析光谱数据集的多模态和多尺度非局部均值方法

提出了一种多模态和多尺度非局部均值 (M3S-NLM) 方法，用于从透射电子显微镜记录的低信噪比 (SNR) 数据集中提取原子分辨光谱图。该方法改进了先前测试过的去噪技术，因为它考虑了同时记录的暗场信号与光谱数据集之间的相关性，而不会影响空间分辨率。M3S-NLM 方法应用于电子能量色散 X 射线和电子能量损失光谱 (EELS) 数据集。我们说明了在 GaN 上生长的 Al1-xInxN 合金中原子尺度扩散过程的恢复以及钙钛矿纳米催化剂的表面氧化态。