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Noise in atomic force microscopy images

Atomic Force Microscopy (AFM) gives a possibility to study and control the surface structure at submicron spatial scales. The essential problem in studying the surfaces is their adequate parameterization. It is necessary to extract information from the surface roughness profiles h(x) and h(y) along coordinates x and y. These profiles contain regular (resonant) components as well as chaotic (noisy) components with "long memory". The main questions are how to extract useful information about the surface state and study the effect of various external factors on it by analyzing the spatial series h(x) and h(y) and separate out the information contents of chaotic and resonant components. These problems can be solved by using Flicker-Noise Spectroscopy (FNS) approach. According to FNS, the information hidden in chaotic surface profiles is represented by correlation links in sequences of different types of irregularities: spikes, jumps, and discontinuities in derivatives of different orders at all spatial hierarchical levels of the systems. In this paper, the FNS is used to parameterize AFM images of sufficiently homogeneous structures obtained for surfaces of lithium fluoride single crystals as well as two dendritic (treelike) structures formed on mica surface from solutions of surfactant copolymers.