OPTIMAL FILTERING OF SCANNING PROBE MICROSCOPE IMAGES FOR WEAR ANALYSIS OF SMOOTH SURFACES

A procedure for removing cumulative drift and white noise from scannin g probe microscope images has been constructed. Smooth amorphous carbo n overcoats on superpolished hard disk media in particular were examin ed using a scanning probe microscope. The surfaces typically had a sim ilar to 1 nm rms roughness over a scan length of 10 mu m. The low roug hness yielded a relatively low signal to noise ratio in the unfiltered image. While a conventional filter removes a great deal of noise, an optimal Fourier (Wiener) filter that more selectively removes noise fr om the image is discussed. White noise and drift were modeled and thei r contributions to the power spectrum are estimated, resulting in an o pen clamshell-shaped two-dimensional filter. The effect of the filter was demonstrated by subjecting filtered images of unworn and worn area s to a smooth surface to second derivative calculations in different d irections. Anisotropy in the wear process associated with the wear dir ection is apparent in the optimally filtered images. (C) 1996 American Vacuum Society.