Fast AFM Imaging Based on Compressive Sensing Using Undersampled Raster Scan

Abstract

Atomic force microscope (AFM), which has nanoscale precision, is a widely used instrument in material science and biomedical science. Nevertheless, conventional AFM scanning is a time-consuming procedure. Compressive sensing (CS) and undersampling techniques have been introduced to accomplish fast AFM imaging in recent years. At present, existing undersampled scan patterns cannot simultaneously guarantee imaging efficiency and quality well. Therefore, a novel one called undersampled raster (USR) scan is put forward in this article. It has higher imaging efficiency than most existing scan patterns, which is drawn by calculating the scanning time with the proposed estimation formulas. Experimental results show that the imaging quality is obviously better than using other combinations of fast scan patterns and reconstruction algorithms when the regular form of the USR scan is employed with Total Variation Minimization by Augmented Lagrangian and Alternating Direction Algorithm (TVAL3). The universality of this imaging scheme is verified by using a variety of samples. In the end, the applications of regular USR scan or its variant for super-resolution AFM imaging and predicting appropriate sampling rates are proposed. In conclusion, applying regular USR scan and TVAL3 algorithm to CS-based AFM can effectively realize fast and high-quality imaging.