An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy

Manuel Schimmack; Paolo Mercorelli; Anthimos Georgiadis

doi:10.1109/MMAR.2016.7575168

An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

2 Zitate (Scopus)

Abstract

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.

Originalsprache	Englisch
Titel	2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
Seitenumfang	6
Herausgeber (Verlag)	IEEE - Institute of Electrical and Electronics Engineers Inc.
Erscheinungsdatum	22.09.2016
Seiten	397 - 402
Aufsatznummer	7575168
ISBN (elektronisch)	978-1-5090-1866-6, 978-1-5090-1715-7
DOIs	https://doi.org/10.1109/MMAR.2016.7575168
Publikationsstatus	Erschienen - 22.09.2016
Veranstaltung	International Conference on Methods and Models in Automation an Robotics - MMAR 2016 - Miedzyzdorje, Polen Dauer: 29.08.2016 → 01.09.2016 Konferenznummer: 21 http://www.ieee-ras.org/component/rseventspro/event/802-mmar-2016-21st-international-conference-on-methods-and-models-in-automation-and-robotics

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10.1109/MMAR.2016.7575168

International Conference on Methods and Models in Automation an Robotics - MMAR 2016
Schimmack, M. (Teilnehmer*in)
29.08.2016 → 01.09.2016
Aktivität: Wissenschaftliche und künstlerische Veranstaltungen › Konferenzen › Forschung

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Schimmack, M., Mercorelli, P., & Georgiadis, A. (2016). An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy. in 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016 (S. 397 - 402). Artikel 7575168 (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MMAR.2016.7575168

Schimmack, Manuel ; Mercorelli, Paolo ; Georgiadis, Anthimos. / An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy. 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016. IEEE - Institute of Electrical and Electronics Engineers Inc., 2016. S. 397 - 402 (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016).

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title = "An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy",

abstract = "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.",

keywords = "Engineering, Atomic Force Microscopy, Discrete wavelet transform method, Noise reduction, Orthogonal wavelets, Surface topography",

author = "Manuel Schimmack and Paolo Mercorelli and Anthimos Georgiadis",

year = "2016",

month = sep,

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doi = "10.1109/MMAR.2016.7575168",

language = "English",

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publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

note = "21st International Conference on Methods and Models in Automation and Robotics (MMAR), MMAR 2016 ; Conference date: 29-08-2016 Through 01-09-2016",

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Schimmack, M , Mercorelli, P & Georgiadis, A 2016, An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy. in 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016., 7575168, 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016, IEEE - Institute of Electrical and Electronics Engineers Inc., S. 397 - 402, International Conference on Methods and Models in Automation an Robotics - MMAR 2016, Miedzyzdorje, Polen, 29.08.16. https://doi.org/10.1109/MMAR.2016.7575168

An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy. / Schimmack, Manuel ; Mercorelli, Paolo ; Georgiadis, Anthimos.
2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016. IEEE - Institute of Electrical and Electronics Engineers Inc., 2016. S. 397 - 402 7575168 (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016).

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

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 - https://www.scopus.com/pages/publications/84991783876

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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 -

Schimmack M , Mercorelli P , Georgiadis A. An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy. in 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016. IEEE - Institute of Electrical and Electronics Engineers Inc. 2016. S. 397 - 402. 7575168. (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016). doi: 10.1109/MMAR.2016.7575168

An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy

Abstract

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International Conference on Methods and Models in Automation an Robotics - MMAR 2016

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