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Images in atomic force microscopy (AFM) are built pixel-by-pixel through a raster scan process and can take on the order of minutes to obtain. The problem of imaging a sample can be characterized as using a short-range or point-like sensor to obtain information about a system over a region and is common across a broad range of fields in science and engineering. In many cases, as in most AFM images, the region to be scanned consists primarily of empty or uninteresting space. In this situation raster-scanning, while easy to implement, is extremely inefficient. It can be viewed as an open-loop scheme because no use is made of data being acquired by the sensor. In this paper, we survey results from the literature describing alternative scanning and sampling approaches. These algorithms often use prior information about the system being measured as well as real-time feedback from previously measured points to keep the sensor in the regions of interest.
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