Feature extraction via similarity search: application to atom finding and denoising in electron and scanning probe microscopy imaging

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...

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Detalles Bibliográficos
Autores principales: Somnath, Suhas, Smith, Christopher R., Kalinin, Sergei V., Chi, Miaofang, Borisevich, Albina, Cross, Nicholas, Duscher, Gerd, Jesse, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846807/
https://www.ncbi.nlm.nih.gov/pubmed/29568723
http://dx.doi.org/10.1186/s40679-018-0052-y
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40679-018-0052-y) contains supplementary material, which is available to authorized users.

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