Signal Processing Challenges and Examples for {\it in-situ} Transmission Electron Microscopy
This work tackles data processing challenges for materials scientists using TEM, but it is incremental as it reviews existing applications and proposes future integration opportunities.
The paper addresses the need for advanced data processing tools to handle high-volume, high-resolution data from Transmission Electron Microscopy (TEM) at microsecond frame rates, highlighting areas in materials science that have benefited from integrating signal processing and statistical analysis with TEM data collection.
Transmission Electron Microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TEM have enabled high-volume and high-resolution data collection at a microsecond frame rate. Taking advantage of these advances in data collection rates requires the development and application of data processing tools, including image analysis, feature extraction, and streaming data processing techniques. In this paper, we highlight a few areas in materials science that have benefited from combining signal processing and statistical analysis with data collection capabilities in TEM and present a future outlook on opportunities of integrating signal processing with automated TEM data analysis.