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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

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.

Original languageEnglish
Title of host publication2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
Number of pages6
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication date22.09.2016
Pages397 - 402
Article number7575168
ISBN (electronic)978-1-5090-1866-6, 978-1-5090-1715-7
DOIs
Publication statusPublished - 22.09.2016
Event21st International Conference on Methods and Models in Automation and Robotics (MMAR) - Miedzyzdorje, Poland
Duration: 29.08.2016 → 01.09.2016
Conference number: 21
http://www.ieee-ras.org/component/rseventspro/event/802-mmar-2016-21st-international-conference-on-methods-and-models-in-automation-and-robotics

    Research areas

  • Engineering
  • Atomic Force Microscopy, Discrete wavelet transform method, Noise reduction, Orthogonal wavelets, Surface topography

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