Paper Title:
Signal Denoising of MEMS Microstructure Profile
  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.

  Info
Periodical
Key Engineering Materials (Volumes 381-382)
Edited by
Wei Gao, Yasuhiro Takaya, Yongsheng Gao and Michael Krystek
Pages
69-72
DOI
10.4028/www.scientific.net/KEM.381-382.69
Citation
K. Hu, X. Q. Jiang, X. J. Liu, "Signal Denoising of MEMS Microstructure Profile", Key Engineering Materials, Vols. 381-382, pp. 69-72, 2008
Online since
June 2008
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Price
$32.00
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