ISSN:
1013-9826
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
A new signal-denoising approach based on DT-CWT (Dual-Tree Complex WaveletTransform) is presented in this paper to extract feature information from microstructure profile. Ittakes advantage of shift invariance of DT-CWT, non-Gaussian probability distribution for thewavelet coefficients and the statistical dependencies between a coefficient and its parent. Thisapproach substantially improved the performance of classical wavelet denoising algorithms, both interms of SNR and in terms of visual artifacts. A simulated MEMS microstructure signal is analyzed
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/01/57/transtech_doi~10.4028%252Fwww.scientific.net%252FKEM.381-382.69.pdf
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