Reconstruction Algorithms in Undersampled AFM Imaging

Thomas Arildsen, Christian Schou Oxvig, Patrick Steffen Pedersen, Jan Østergaard, Torben Larsen

Research output: Contribution to journalJournal articleResearchpeer-review

21 Citations (Scopus)
496 Downloads (Pure)


This paper provides a study of spatial undersampling in atomic force microscopy (AFM) imaging followed by different image reconstruction techniques based on sparse approximation as well as interpolation. The main reasons for using undersampling is that it reduces the path length and thereby the scanning time as well as the amount of interaction between the AFM probe and the specimen. It can easily be applied on conventional AFM hardware. Due to undersampling, it is then necessary to further process the acquired image in order to reconstruct an approximation of the image. Based on real AFM cell images, our simulations reveal that using a simple raster scanning pattern in combination with conventional image interpolation performs very well. Moreover, this combination enables a reduction by a factor 10 of the scanning time while retaining an average reconstruction quality around 36 dB PSNR on the tested cell images.
Translated title of the contributionRekonstruktionsalgoritmer i undersamplet AFM billeddannelse
Original languageEnglish
JournalI E E E Journal on Selected Topics in Signal Processing
Issue number1
Pages (from-to)31-46
Publication statusPublished - 1 Feb 2016


  • Atomic Force Microscopy
  • undersampling
  • Image Reconstruction
  • sparse approximation
  • Interpolation
  • Compressed Sensing


Dive into the research topics of 'Reconstruction Algorithms in Undersampled AFM Imaging'. Together they form a unique fingerprint.

Cite this