Enhanced feature analysis using wavelets for scanning probe microscopy images of surfaces

In this work we develop wavelet theory for the analysis of surface topography images obtained by scanning probe microscopy (SPM) such as atomic force microscopy (AFM). Wavelet transformation is localized in space and frequency, which can offer an advantage for analyzing information on surface morphology and topography. Wavelet transformation is an ideal tool to detect trends, discontinuities, and short periodicities on a surface. Additionally, wavelets can be used to remove artifacts and noise from scanning microscopy images. In terms of 3-D image analysis, discrete wavelet transform can capture patterns at all relevant frequency scales, thus providing a level of image analysis that is not possible otherwise. It is also possible to use the methodology for analyzing surface structures at the molecular level. The results demonstrate superior capabilities of wavelet approach to scanning probe microscopy image analysis compared to traditional analysis techniques.