Reconstruction Algorithms in Undersampled AFM Imaging

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

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Abstract

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.
Original languageEnglish
JournalI E E E Journal on Selected Topics in Signal Processing
Volume10
Issue number1
Pages (from-to)31-46
ISSN1932-4553
DOIs
Publication statusPublished - 1 Feb 2016

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Atomic force microscopy
Imaging techniques
Scanning
Interpolation
Image reconstruction
Hardware

Keywords

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

Cite this

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title = "Reconstruction Algorithms in Undersampled AFM Imaging",
abstract = "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.",
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Reconstruction Algorithms in Undersampled AFM Imaging. / Arildsen, Thomas; Oxvig, Christian Schou; Pedersen, Patrick Steffen; Østergaard, Jan; Larsen, Torben.

In: I E E E Journal on Selected Topics in Signal Processing, Vol. 10, No. 1, 01.02.2016, p. 31-46.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Reconstruction Algorithms in Undersampled AFM Imaging

AU - Arildsen, Thomas

AU - Oxvig, Christian Schou

AU - Pedersen, Patrick Steffen

AU - Østergaard, Jan

AU - Larsen, Torben

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N2 - 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.

AB - 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.

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KW - undersampling

KW - Image Reconstruction

KW - sparse approximation

KW - Interpolation

KW - Compressed Sensing

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