Signal Denoising of MEMS Microstructure Profile |
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| Journal | Key Engineering Materials (Volumes 381 - 382) |
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| Volume | Measurement Technology and Intelligent Instruments VIII |
| 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 | Kai Hu et al., 2008, Key Engineering Materials, 381-382, 69 |
| Online since | June, 2008 |
| Authors | Kai Hu, Xiang Qian Jiang, Xiao Jun Liu |
| Keywords | DT-CWT, MEME Microstructure, Micro Metrology, Nano Metrology |
| 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. |
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