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We have developed a real-space method to correct distortion due to thermaldrift and piezoelectric actuator nonlinearities on scanning tunnelingmicroscope images using Matlab. The method uses the known structures typicallypresent in high-resolution atomic and molecularly-resolved images as aninternal standard. Each image feature (atom or molecule) is first identified inthe image. The locations of each feature's nearest neighbors (NNs) are used tomeasure the local distortion at that location. The local distortion map acrossthe image is simultaneously fit to our distortion model, which includes thermaldrift in addition to piezoelectric actuator hysteresis and creep. The imagecoordinates of the features and image pixels are corrected using an inversetransform from the distortion model. We call this technique the thermal-drift,hysteresis, and creep transform (DHCT). Performing the correction in real spaceallows defects, domain boundaries, and step edges to be excluded with a spatialmask. Additional real-space image analyses are now possible with thesecorrected images. Using graphite(0001) as model system, we show lattice fittingto the corrected image, averaged unit cell images, and symmetry-averaged unitcell images. Statistical analysis of the distribution of the image featuresaround their best-fit lattice sites measures the aggregate noise in the image,which can be expressed as feature confidence ellipsoids.

Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images