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

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

Authors

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.

OriginalspracheEnglisch
Titel2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
Anzahl der Seiten6
VerlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Erscheinungsdatum22.09.2016
Seiten397 - 402
Aufsatznummer7575168
ISBN (elektronisch)978-1-5090-1866-6, 978-1-5090-1715-7
DOIs
PublikationsstatusErschienen - 22.09.2016
VeranstaltungInternational 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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