Automated spatial drift correction for EFTEM image series

Energy filtering transmission electron microscopy (EFTEM) is a widely used technique in many areas of scientific research. Image contrast in energy-filtered images arises from specific scattering events such as the ionization of atoms. By combining a set of two or more images, relative sample thickness maps or elemental distribution maps can be easily created. It is also possible to acquire a whole series of energy-filtered images to do more complex data analysis. However, whenever several images are combined to extract certain information, problems are introduced due to sample drift between the exposures. In order to obtain artifact-free information, this spatial drift has to be taken care of. Manual alignment by overlaying and shifting the images to find the best overlap is usually very accurate but extremely time consuming for larger data sets. When large amounts of images are recorded in an EFTEM series, manual correction is no longer a reasonable option. Hence, automatic routines have been developed that are mostly based on the cross-correlation algorithm. Existing routines, however, sometimes fail and again make time consuming manual adjustments necessary. In this paper we describe a new approach to the drift correction problem by incorporating a statistical treatment of the data and we present our statistically determined spatial drift (SDSD) correction program. We show its improved performance by applying it to a typical EFTEM series data block.