基于高斯过程模型的高光谱扫描探针显微镜成像机理
Imaging Mechanism for Hyperspectral Scanning Probe Microscopy via Gaussian Process Modelling
摘要：
我们调查的能力，重建和推导空间结构从稀疏采样的3D piezoresponse力显微镜数据，捕获使用带激励（BE）技术，通过高斯过程（GP）的方法。即使对于弱信息先验，GP方法允许在空间域和频域中明确确定成像过程的特征长度尺度。我们进一步表明，BE数据集往往是过采样的，原始数据集的约30%足以进行高质量的重建，有可能实现更快的BE成像。最后，我们讨论了如何GP可以用于SPM的自动化实验，结合GP回归与非矩形扫描。应用于高光谱数据的GP回归的完整代码可在https://git.io/JePGr上获得。
英文摘要：
We investigate the ability to reconstruct and derive spatial structure from sparsely sampled 3D piezoresponse force microcopy data, captured using the band-excitation (BE) technique, via Gaussian Process (GP) methods. Even for weakly informative priors, GP methods allow unambiguous determination of the characteristic length scales of the imaging process both in spatial and frequency domains. We further show that BE data set tends to be oversampled, with ~30% of the original data set sufficient for high-quality reconstruction, potentially enabling the faster BE imaging. Finally, we discuss how the GP can be used for automated experimentation in SPM, by combining GP regression with non-rectangular scans. The full code for GP regression applied to hyperspectral data is available at https://git.io/JePGr.
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