We develop an algorithm for feature extraction based on structural similarity and demonstrate its application for atom and pattern finding in high-resolution electron and scanning probe microscopy images. The use of the combined local identifiers formed from an image subset and appended Fourier, or other transform, allows tuning selectivity to specific patterns based on the nature of the recognition task. The proposed algorithm is implemented in Pycroscopy, a community-driven scientific data analysis package, and is accessible through an interactive Jupyter notebook available on GitHub.

中文翻译：

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通过相似性搜索进行特征提取：应用于电子和扫描探针显微镜成像中的原子发现和去噪。

我们开发了一种基于结构相似性的特征提取算法，并演示了其在高分辨率电子和扫描探针显微镜图像中寻找原子和图案的应用。由图像子集和附加的傅立叶或其他变换形成的组合的局部标识符的使用允许基于识别任务的性质将选择性调谐到特定模式。提出的算法在Pycroscopy中实现，Pycroscopy是一个社区驱动的科学数据分析程序包，可通过GitHub上的交互式Jupyter笔记本进行访问。