An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016. IEEE - Institute of Electrical and Electronics Engineers Inc., 2016. p. 397 - 402 7575168 (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy
AU - Schimmack, Manuel
AU - Mercorelli, Paolo
AU - Georgiadis, Anthimos
N1 - Conference code: 21
PY - 2016/9/22
Y1 - 2016/9/22
N2 - This paper deals with the noise reduction of discrete AFM surface images using orthogonal wavelets. More in detail, it compares the usefulness of the Daubechies wavelets with different vanishing moments for noise reduction. The work is based upon the discrete wavelet transform (DWT) version of wavelet package transform (WPT). With the help of a seminorm the measurement of noise of a sequence is defined. An algorithm for noise reduction is proposed to detect unavoidable measured noise in topographic surface scans. The denoising wavelet algorithm is used to improve the quality of the scanned images. By taking real measurements in which the measurement and system noise is included, the effectiveness of the proposed denoising algorithm is validated.
AB - This paper deals with the noise reduction of discrete AFM surface images using orthogonal wavelets. More in detail, it compares the usefulness of the Daubechies wavelets with different vanishing moments for noise reduction. The work is based upon the discrete wavelet transform (DWT) version of wavelet package transform (WPT). With the help of a seminorm the measurement of noise of a sequence is defined. An algorithm for noise reduction is proposed to detect unavoidable measured noise in topographic surface scans. The denoising wavelet algorithm is used to improve the quality of the scanned images. By taking real measurements in which the measurement and system noise is included, the effectiveness of the proposed denoising algorithm is validated.
KW - Engineering
KW - Atomic Force Microscopy
KW - Discrete wavelet transform method
KW - Noise reduction
KW - Orthogonal wavelets
KW - Surface topography
UR - http://www.scopus.com/inward/record.url?scp=84991783876&partnerID=8YFLogxK
U2 - 10.1109/MMAR.2016.7575168
DO - 10.1109/MMAR.2016.7575168
M3 - Article in conference proceedings
T3 - 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
SP - 397
EP - 402
BT - 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
PB - IEEE - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International Conference on Methods and Models in Automation and Robotics (MMAR)
Y2 - 29 August 2016 through 1 September 2016
ER -