Paper
26 October 1999 Coefficient denoising method with wavelet transform
Amid Bakhtazad, Jose A. Romagnoli
Author Affiliations +
Abstract
In this paper, the recovery of noisy process data or de- noising using wavelets is studied. In addition, the effectiveness of some wavelet-based modern algorithms of process data recovery is experimented. A novel approach in de-noising according to the WienerShrink method of wavelet coefficients thresholding is suggested. Finally, the results of computer simulation for a special case study and comparing the mean square errors of the algorithms are presented. Two Continuous Stirred Tank Reactors in series with an intermediate mixer, are considered as a case study. The results show the advantages of our method over the previous wavelet-based approaches.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amid Bakhtazad and Jose A. Romagnoli "Coefficient denoising method with wavelet transform", Proc. SPIE 3813, Wavelet Applications in Signal and Image Processing VII, (26 October 1999); https://doi.org/10.1117/12.366831
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data processing

Wavelets

Wavelet transforms

Filtering (signal processing)

Denoising

Nonlinear filtering

Data analysis

RELATED CONTENT

Multiple target tracking using an extended Kalman filter
Proceedings of SPIE (October 01 1990)
Improved wavelet denoising via empirical Wiener filtering
Proceedings of SPIE (October 30 1997)
Wavelet denoising of pulsed laser radar signals
Proceedings of SPIE (November 04 2010)
Rational wavelet transform: application to signal denoising
Proceedings of SPIE (February 27 2004)
SURE threshold for denoising complex signals with Waveshrink
Proceedings of SPIE (September 25 2003)
Two step local Wiener filter using dual tree complex wavelet...
Proceedings of SPIE (September 08 2011)

Back to Top