Reconstruction Algorithms in Undersampled AFM Imaging

被引：24

作者：

Arildsen, Thomas ^{[1
]}

Oxvig, Christian Schou ^{[1
]}

Pedersen, Patrick Steffen ^{[1
]}

Ostergaard, Jan ^{[1
]}

Larsen, Torben ^{[1
]}

机构：

[1] Aalborg Univ, Fac Sci & Engn, Dept Elect Syst, DK-9100 Aalborg, Denmark

来源：

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING | 2016年 / 10卷 / 01期

关键词：

Atomic force microscopy; undersampling; image reconstruction; sparse approximation; interpolation; compressed sensing; SCANNING PROBE MICROSCOPY; ATOMIC-FORCE MICROSCOPY; POSITION SENSOR; DECOMPOSITION; RECOVERY; PURSUIT; !text type='PYTHON']PYTHON[!/text; MODEL; SPEED;

D O I：

10.1109/JSTSP.2015.2500363

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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 necessary to subsequently 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.

引用

页码：31 / 46

页数：16

共 99 条

[21] Performance comparisons of greedy algorithms in compressed sensing
Blanchard, Jeffrey D.
Tanner, Jared
[J]. NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS, 2015, 22 (02) : 254 - 282
[22] Iterative Thresholding for Sparse Approximations
Blumensath, Thomas
Davies, Mike E.
[J]. JOURNAL OF FOURIER ANALYSIS AND APPLICATIONS, 2008, 14 (5-6) : 629 - 654
[23] Bo Song, 2011, 2011 IEEE 11th International Conference on Nanotechnology (IEEE-NANO), P1056, DOI 10.1109/NANO.2011.6144587
[24] Boyd S., 2004, CONVEX OPTIMIZATION
[25] Robust uncertainty principles:: Exact signal reconstruction from highly incomplete frequency information
Candès, EJ
Romberg, J
Tao, T
[J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 2006, 52 (02) : 489 - 509
[26] The restricted isometry property and its implications for compressed sensing
Candes, Emmanuel J.
[J]. COMPTES RENDUS MATHEMATIQUE, 2008, 346 (9-10) : 589 - 592
[27] Candès EJ, 2008, IEEE SIGNAL PROC MAG, V25, P21, DOI 10.1109/MSP.2007.914731
[28] Compressed sensing with coherent and redundant dictionaries
Candes, Emmanuel J.
Eldar, Yonina C.
Needell, Deanna
Randall, Paige
[J]. APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS, 2011, 31 (01) : 59 - 73
[29] Chen A., 2013, Excursions in Harmonic Analysis, V2, P311, DOI DOI 10.1007/978-0-8176-8379-5_
[30] Application of atomic force microscopy to living samples from cells to fresh tissues
Chen PeiPei
Dong HongTao
Chen Long
Sun QuanMei
Han Dong
[J]. CHINESE SCIENCE BULLETIN, 2009, 54 (14): : 2410 - 2415

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