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 language | English |
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| Title of host publication | 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016 |
| Number of pages | 6 |
| Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
| Publication date | 22.09.2016 |
| Pages | 397 - 402 |
| Article number | 7575168 |
| ISBN (electronic) | 978-1-5090-1866-6, 978-1-5090-1715-7 |
| DOIs | |
| Publication status | Published - 22.09.2016 |
| Event | 21st 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 |
- Engineering
- Atomic Force Microscopy, Discrete wavelet transform method, Noise reduction, Orthogonal wavelets, Surface topography