Abstract

High-speed scanning tunneling microscopy (STM) data have become available that provide movies of time-dependent surface processes. To track adsorbed atoms and molecules in such data automatic routines are required. We introduce a multiresolution wavelet particle detection algorithm for this purpose. To identify the particles, the images are decomposed by means of a discrete wavelet transform into wavelet planes of different resolutions. An ‘à trous’ low-pass filter is applied. The coefficients from the wavelet planes are filtered to remove noise. Wavelet planes with significant coefficients from the particles are multiplied, and the product is transformed into a binary particle mask. The precision of the method is tested with data sets of adsorbed CO molecules and O atoms on a Ru(0001) surface. The algorithm can safely detect and localize these particles with high precision, even in the presence of the enhanced noise characteristic for high-speed, constant-height STM data. By linking the particle positions, we obtain extended trajectories with a resolution of ∼0.5 Å or better allowing us to investigate the detailed motion of single atoms on a surface.

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