Atomic Force Microscopy (AFM) is one of the most advanced tools for high-resolution imaging and manipulation of nanoscale matter. Unfortunately, standard AFM imaging requires a timescale on the order of minutes to hours to acquire an image which makes it unsuitable for observing dynamic processes. Moreover it is often required to take several images before a suitable image region is found. This significantly reduces the advantages of AFM. With this project, we propose to use compressive sensing and efficient computing in order to provide fast imaging. A simple proof of concept study has verified the potential of the proposed method. To improve the reconstruction performance, probabilistic methods are utilized, and the sampling patterns and dictionaries are jointly designed. The project employs two PhD students and one post-doc at AAU, and has international collaboration with AccelerEyes, USA, and Mississippi State University, USA.
The project is funded by The Danish Council for Independent Research | Technology and Production Sciences under grant number 1335-00278A / 12-134971.