2012
DOI: 10.4172/2169-0022.s1.006
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Enhancement and recovery in atomic force microscopy images

Abstract: Summary. Atomic force microscopy (AFM) images have become increasingly useful in the study of biological, chemical and physical processes at the atomic level. The acquisition of AFM images takes more time than the acquisition of most optical images, so that the avoidance of unnecessary scanning becomes important. Details that are unclear from a scan may be enhanced using various image processing techniques. This chapter reviews various interpolation and inpainting methods and considers them in the specific app… Show more

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Cited by 7 publications
(5 citation statements)
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“…There are numerous image reconstruction methods available for use with data obtained from non-raster scanning patterns, and the ideal choice largely depends on the sample under study. A comparison of various methods, including inpainting and compressive-sensing-based reconstructions for AFM images can be found in [ 28 , 29 ]. For all images in this paper, we made use of heat equation inpainting to carry out interpolation, as it produced reliable and high quality images at a low computational cost [ 30 ].…”
Section: Methodsmentioning
confidence: 99%
“…There are numerous image reconstruction methods available for use with data obtained from non-raster scanning patterns, and the ideal choice largely depends on the sample under study. A comparison of various methods, including inpainting and compressive-sensing-based reconstructions for AFM images can be found in [ 28 , 29 ]. For all images in this paper, we made use of heat equation inpainting to carry out interpolation, as it produced reliable and high quality images at a low computational cost [ 30 ].…”
Section: Methodsmentioning
confidence: 99%
“…Once the data has been collected, a complete image must be generated from the sub-sampled data. Once again there are a variety of methods for achieving this with the two main groups of algorithms being inpainting and sparse reconstruction (Chen et al 2012;Luo and Andersson 2015). Inpainting schemes seek to fill in missing data using information from nearby pixels.…”
Section: Sub-sampling the Imagementioning
confidence: 99%
“…It is wellknown that the classic inpainting models including TV models [5,41], have difficulty in connecting the thin objects [11,12] (see Figure 1, 'TV' inpainting). Thus inpainting methods involving higher order information [11,40], such as curvature, were proposed to improve the results.…”
Section: Insight On the Modelmentioning
confidence: 99%