A comparative study of noise effect on wavelet based de-noising methods

TIC-STH'09: 2009 IEEE Toronto International Conference - Science and Technology for Humanity

Volumn , Issue , 2009, Pages 919-926

  Xie, Shengkun ^a   Liò, Pietro ^b   Lawniczak, Anna T ^a  

^a UNIVERSITY OF GUELPH   (Canada)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL DATA; COMPARATIVE STUDIES; DE-NOISING; DENOISING METHODS; KNOW-HOW; LONG MEMORIES; MULTI-SCALE PRINCIPAL COMPONENT ANALYSIS; MULTI-SCALE STRUCTURES; NOISE EFFECTS; NOISE LEVELS; NOISY SIGNALS; NON-STATIONARITIES; NONGAUSSIANITY; SELF-SIMILARITIES; WAVELET BASIS FUNCTIONS; WAVELET DENOISING; WAVELET THRESHOLDING;

TECHNOLOGICAL FORECASTING; TEMPERATURE INDICATING CAMERAS; WAVELET ANALYSIS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 77952708588     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/TIC-STH.2009.5444365     Document Type: Conference Paper

References (27)

1. W.E. Leland, M.S. Taqqu, W. Willinger and D. V. Willson, On the self-similar nature of Ethernet traffic, Computer Communications Review, 23, 183-193, 1993.
2. M.S. Taqqu, V. Teverovsky and W. Willinger, Is network traffic self-similar or multifractal?, Fractals, vol.5, 63-74, 1997. 3.
3. P. Abry and D. Veitch, Wavelet Analysis of long-range dependent traffic, IEEE Trans. On Into. Theory, 44(1), 2-15, 1998. 5.
4. A. Erramilli, O. Narayan, A. Neidhardt and Saniee, Performance Impacts of Multi-Scaling in Wide Area TCP/IP Traffic, Proceedings of IEEE Infocom 2000, Tel Aviv, Israel, March 2000.
5. J.O. Ramsay and B.W. Silverman, Functional Data Analysis, Springer-Verlag, New york, 2002.
6. S. Xie, A. T. Lawniczak and P. Lio', Parametric & Non-parametric Analysis of Mean Treatment Effects of Number of Packets in Transit in Data Network Model, Proc. of the 21th IEEE CCECE 2008-CCGEI 2008.
7. P. Abry, R. Baraniuk, P. Flandrin, R. Riedi and D. Veitch, The Multiscale Nature of Network Traffic: Discovery, Analysis, and Modeling, IEEE Signal Processing Magazine 19(3), 28-46, 2002.
8. B. Vidakovic, Statistical Modeling by Wavelets, John Wiley & Sons, Inc. 1999.
9. D. P. Percival and A.T. Walden, Wavelet Methods for Time Series Analysis, Cambridge Univ. Press, New York, 2000.
10. P. Lio', A. T. Lawniczak, S. Xie and J. Xu, Wavelet domain statistics of packet switching networks near traffic congestion, BIOWIRE 2007, LNCS 5151, Springer-Verlag, pp.256-267, 2008.
11. Wink, Alle Meije; Roerdink, Jos B.T.M.2, Denoising Functional MR Images: A Comparison of Wavelet Denoising and Gaussian Smoothing. IEEE Transactions on Medical Imaging, vol.23, no. 3, pp. 374-387, 2004.
12. J. Hesamoddin; S. Hamid; H. Gholam Ali, Noise suppression of fMRI time-series in wavelet domain, Proceedings of the Seventh IASTED International Conference on Signal and Image Processing, SIP 2005, pp. 136-138, 2005.
13. V. Gupta, Vikas; C. C. Chan; C. Poh; T. H. Chow; T. C. Meng; N. B. Koon, Computerized automation of wavelet based denoising method to reduce speckle noise in OCT images. 5th Int. Conference on Information Technology and Applications in Biomedicine, ITAB 2008 in conjunction with 2nd Int. Symposium and Summer School on Biomedical and Health Engineering, IS3BHE 2008, pp. 120-123, 2008.
14. D. Donoho, I. Johnstone, G. Kerkyacharian and D. Picard, Wavelet shrinkage: Asymptopia? J. R. Statist. Soc. B, 57, 301-369, 1995.
15. D. Donoho, I. Johnstone, Minimax estimation via wavelet shrinkage. Ann. Statist., 26, 879-921, 1998.
16. J.L. Starck, F. Murtagh and A. Bijaoui, Image Processing and Data Analysis: The Multiscale Approach, Cambridge University Press, 1998.
17. T. Chan and J. Shen, Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods, SIAM, 2005.
18. B. W. Suter, Multirate and Wavelet Signal Processing (Wavelet Analysis and Its Applications), Academic Press, 1998.
19. S. Mallat, A Wavelet Tour of Signal Processing, Academic Press, 1999.
20. M. Weeks, Digital Signal Processing Using Matlab and Wavelets, Infinity Science Press, 2006. 25.
21. I. Daubechies, Ten Lectures On Wavelets. SIAM, Philadelfia, 1992.
22. I.T. Jolliffe, Principal Component Analysis, Springer Science+Bussiness Media, Inc., New York, 2004.
23. A. Hyvarinen, J. Karhunen and E. Oja. Independent Component Analysis, John Wiley & Sons Inc., New York, 2001.
24. B. Bakshi, Multiscale PCA with application to MSPC monitoring, AIChE J., 44, pp. 1596-1610, 1998.
25. B. Bakshi. Multiscale analysis and modeling using wavelets. Journal of chemometrics 13.3-4, 415-434, 1999.
26. A. T. Lawniczak and S. Xie, Study of Number of Packets in Transit in a Data Network Model Near Onset of Congestion Using Functional Fixed Effect Models, Proc. of the 21th IEEE CCECE 2008-CCGEI 2008.
27. J. D. Hamilton, Time Series Analysis, Chapter 21, Section 2, ISBN 0-691-04289-6, Princeton U Press, 1994.