Structure Assisted Compressed Sensing Reconstruction of Undersampled AFM Images

Christian Schou Oxvig, Thomas Arildsen, Torben Larsen

Research output: Contribution to journalJournal articleResearchpeer-review

16 Citations (Scopus)


The use of compressed sensing in atomic force microscopy (AFM) can potentially speed-up image acquisition, lower probe-specimen interaction, or enable super resolution imaging. The idea in compressed sensing for AFM is to spatially undersample the specimen, i.e. only acquire a small fraction of the full image of it, and then use advanced computational techniques to reconstruct the remaining part of the image whenever this is possible. Our initial experiments have shown that it is possible to leverage inherent structure in acquired AFM images to improve image reconstruction. Thus, we have studied structure in the discrete cosine transform coefficients of typical AFM images. Based on this study, we propose a generic support structure model that may be used to improve the quality of the reconstructed AFM images. Furthermore, we propose a modification to the established iterative thresholding reconstruction algorithms that enables the use of our proposed structure model in the reconstruction process. Through a large set of reconstructions, the general reconstruction capability improvement achievable using our structured model is shown both quantitatively and qualitatively. Specifically, our experiments show that our proposed algorithm improves over established iterative thresholding algorithms by being able to reconstruct AFM images to a comparable quality using fewer measurements or equivalently obtaining a more detailed reconstruction for a fixed number of measurements.
Translated title of the contributionStruktur-assisteret compressed sensing rekonstruktion af under-samplede AFM-billeder
Original languageEnglish
Pages (from-to)1-9
Publication statusPublished - Jan 2017


  • atomic force microscopy (AFM)
  • compressed sensing
  • compressive sampling
  • undersampling
  • Image Reconstruction
  • sparsity modelling

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    • 1 Visiting another research institution

    Cambridge University

    Thomas Arildsen (Visiting researcher)

    20 Sep 201622 Sep 2016

    Activity: Visiting another research institution

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