Reconstruction Algorithms in Undersampled AFM Imaging

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

doi:10.1109/JSTSP.2015.2500363

Reconstruction Algorithms in Undersampled AFM Imaging

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

Department of Electronic Systems

Research output: Contribution to journal › Journal article › Research › peer-review

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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.

Translated title of the contribution	Rekonstruktionsalgoritmer i undersamplet AFM billeddannelse
Original language	English
Journal	I E E E Journal on Selected Topics in Signal Processing
Volume	10
Issue number	1
Pages (from-to)	31-46
ISSN	1932-4553
DOIs	https://doi.org/10.1109/JSTSP.2015.2500363
Publication status	Published - 1 Feb 2016

Keywords

Atomic Force Microscopy
undersampling
Image Reconstruction
sparse approximation
Interpolation
Compressed Sensing

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Arildsen2016Accepted author manuscript, 4.41 MBLicence: Unspecified

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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.",

keywords = "Atomic Force Microscopy, undersampling, Image Reconstruction, sparse approximation, Interpolation, Compressed Sensing",

author = "Thomas Arildsen and Oxvig, {Christian Schou} and Pedersen, {Patrick Steffen} and Jan {\O}stergaard and Torben Larsen",

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AU - Arildsen, Thomas

AU - Oxvig, Christian Schou

AU - Pedersen, Patrick Steffen

AU - Østergaard, Jan

AU - Larsen, Torben

PY - 2016/2/1

Y1 - 2016/2/1

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.

KW - Atomic Force Microscopy

KW - undersampling

KW - Image Reconstruction

KW - sparse approximation

KW - Interpolation

KW - Compressed Sensing

UR - https://doi.org/10.5281/zenodo.32959

UR - https://doi.org/10.5281/zenodo.32958

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DO - 10.1109/JSTSP.2015.2500363

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JO - I E E E Journal on Selected Topics in Signal Processing

JF - I E E E Journal on Selected Topics in Signal Processing

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ER -

Reconstruction Algorithms in Undersampled AFM Imaging

Abstract

Keywords

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FastAFM: Enabling Fast Image Acquisition for Atomic Force Microscopy using Compressed Sensing