Signal Denoising of MEMS Microstructure Profile

X. Q. Jiang, K. Hu, X. J. Liu

Research output: Contribution to journalArticle

Abstract

A new signal-denoising approach based on DT-CWT (Dual-Tree Complex Wavelet Transform) is presented in this paper to extract feature information from microstructure profile. It takes advantage of shift invariance of DT-CWT, non-Gaussian probability distribution for the wavelet coefficients and the statistical dependencies between a coefficient and its parent. This approach substantially improved the performance of classical wavelet denoising algorithms, both in terms of SNR and in terms of visual artifacts. A simulated MEMS microstructure signal is analyzed.

LanguageEnglish
Pages69-72
Number of pages4
JournalKey Engineering Materials
Volume381-382
Publication statusPublished - 17 Jul 2008

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Signal denoising
Wavelet transforms
MEMS
Microstructure
Invariance
Probability distributions

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Jiang, X. Q. ; Hu, K. ; Liu, X. J. / Signal Denoising of MEMS Microstructure Profile. In: Key Engineering Materials. 2008 ; Vol. 381-382. pp. 69-72.
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Jiang, XQ, Hu, K & Liu, XJ 2008, 'Signal Denoising of MEMS Microstructure Profile', Key Engineering Materials, vol. 381-382, pp. 69-72.

Signal Denoising of MEMS Microstructure Profile. / Jiang, X. Q.; Hu, K.; Liu, X. J.

In: Key Engineering Materials, Vol. 381-382, 17.07.2008, p. 69-72.

Research output: Contribution to journalArticle

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