Análise de Métodos de Redução de Ruído por Limiar no Domínio Wavelet
DOI:
https://doi.org/10.5540/tema.2008.09.03.0471Abstract
Neste trabalho é apresentado uma análise e comparação entre os métodos de redução de ruído baseados em corte por limiar no domínio wavelet. O objetivo é apresentar os diversos métodos de redução de ruído, uma vez que nem todos são conhecidos na literatura especializada, indicando os mais eficientes.References
[1] V. Balakrishnan, N. Borges, L. Parchment, “Wavelet Denoising and Speech Enhancement”, Spring, 2006.
K. Dae-Sung, C. Jung-Go, R. Geun-Taek, B. Mun-Seob, B. Hyeon-Deok, Noise reduction using coefficients smoothing wavelet transform, in “Internation Conference on Signal Processing Applications and Technology, (ICSPAT-2002)”, pp. 29-33, San Jose California, 2002.
I. Daubechies, “Ten Lectures on Wavelets”, SIAM, 1992.
D.L. Donoho, De-noising by soft-thresholding, IEEE Transactions on Information Theory, 41, No. 3 (1995), 613-627.
D.L. Donoho, I.M. Johnstone, Ideal spatial adaptation via wavelet shrinkage Biometrika, 81, No. 3, (1994), 425-455.
M.A.Q. Duarte, L.C.O. de Oliveira, F. Villarreal, L.A. Díaz, Compressão de sinais elétricos usando a transformada de wavelet, TEMA - Tendências em Matemática Aplicada e Computacional, 4, No. 1 (2003), 21-30.
M.A.Q. Duarte, “Redução de Ruído em Sinais de Voz no Domínio Wavelet”, Tese de Doutorado, FEIS, UNESP, SP, 2005.
H.Y. Gao, A. Bruce, Waveshrink with firm shrinkage, Statistica Sinica, 7, (1997), 855-874.
J. Vieira Filho, “Redução de Ruído em Sinais de Voz nos Sistemas RádioMóveis Veiculares”, Tese de Doutorado, FEEC-DC, UNICAMP, Campinas, SP, 1996.
Y. Nievergelt, “Wavelets Made Easy”, Birkhauser, Boston, 1999.
F. Nordstr¨om, “Time and Frequency Dependent Noise Reduction Speech Signals”, Master thesis, Department of Mathematical Statistics, Lund Institute of Technology, Lund, Sweden, 2002.
O. Rioul, M. Vetterli, Wavelets and signal processing, Signal Processing Ma- gazine IEEE, 8, No. 4 (1991), 14-38.
H. Sheikhzadeh, H.R. Abutalebi,An improved waveletased speech enhancement system, em “Eurospeech 2001”, pp. 1855-1858, 2001.
H. Storm, “Noise reduction of speech signals with wavelets”, Technical Report No. 1998-02/ISSN 0347-2809, Department of Mathematics, Chalmers University of Techology and Gothenburg University, Gothenburg, Sweden, 1998.
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