Noise Estimation and Reduction in Heart Sounds Using Time Frequency Block Thresholding Method

Authors

  • M. Vishwanath Shervegar Assistant Professor, E&C, MIT, Kundapura, Udupi, Karnataka
  • Ganesh V Bhat Principal, CEC, Mangalore, D.K., Karnataka

DOI:

https://doi.org/10.51983/ajes-2016.5.1.1968

Keywords:

Block thresholding, Activity detection, soft thresholding, overlapping group shrinkage

Abstract

In this paper a novel method of de-noising phonocardiogram by time-frequency Overlapping Group Shrinkage method is described. In this method sigma, the standard deviation of the stationary noise present in a noisy phonocardiogram is found using activity detection. This noise is then canceled by attenuating it in the time frequency domain. The accuracy of noise reduction is measured by SNR. Overlapping Group shrinkage algorithm reduces the effect of noise by attenuating them using hard or soft thresholding. Performance of this method was found to be far better compared to other methods such as Soft Thresholding and Block Thresholding.

References

http://www.peterjbentley.com/heartchallenge/

Bowon Lee Hewlett-Packard Laboratories 1501 Page Mill Rd.Palo Alto, CA 94304 [email protected], Mark Hasegawa-Johnson University of Illinois at Urbana-Champaign Electrical and Computer Engineering 405 N. Mathews Ave,. Urbana, IL61801 [email protected], MINIMUM MEAN-SQUARED ERROR A POSTERIORI ESTIMATION OF HIGH VARIANCE VEHICULAR NOISE

Guoshen Yu, Stéphane Mallat, Fellow, IEEE, and Emmanuel Bacry, Audio Denoising by Time-Frequency Block Thresholding, IEEE Transactions On Signal Processing, Vol. 56, No. 5, May 2008.

Javier Ramírez, José C. Segura, Senior Member, IEEE, Carmen Benítez, Member, IEEE, Luz García, and Antonio Rubio, Senior Member, IEEE Statistical Voice Activity Detection Using a Multiple Observation Likelihood Ratio Test, IEEE Signal Processing Letters, Vol. 12, No. 10, October 2005

Eric Martin, Marie de Masson d'Autume, Christophe Varray, “Audio denoising algorithm with block thresholding”, Published in Image Processing On Line on 2012, July 2 ISSN 2105-1232 ©2012 IPOL.

Po-Yu Chen and Ivan W. Selesnick, Polytechnic Institute of New York University, 6 Metrotech Center, Brooklyn, NY 11201, USA. Email: [email protected], [email protected]. Tel: +1 718 260-3416. Translation-Invariant Shrinkage/Thresholding of Group Sparse Signals.

J. Sohn and W. Sung, “A voice activity detector employing soft decision based noise spectrum adaptation”, Proc. Int. Conf. Acoust., Speech, and Sig. Process., pp.365-368, 1998.

D. L. Donoho. De-noising by soft-thresholding. IEEE Trans. on Information Theory, 41(3):613{627, May 1995.

M. Figueiredo and R. Nowak. Wavelet-based image estimation: An empirical Bayes approach Using Jerey’s noninformative prior. IEEE Trans. Image Process., 10(9):1322{1331, September 2001.

H. Gao. Wavelet shrinkage denoising using the nonnegative garrote. J. Comput. Graph. Statist., 7:469-488, 1998. [11] J. M. Fadili and L. Boubchir. Analytical form for a BayesianWavelet estimator of images using the Bessel K form densities. IEEE Trans. Image Process., 14(2):231{240, February 2005.

A. Hyvvarinen. Sparse code shrinkage: Denoising of non-Gaussian data by maximum likelihood estimation. Neural Computation, 11:1739{1768, 1999.

S. Mallat. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. [14]. S. Boll, “Suppression of acoustic noise in speech using spectral subtraction,” IEEE Trans. Acoustics, Speech, Signal Process., vol. ASSP-27, no. 2, pp. 113– 120, Apr. 1979.

S. Boll, “Suppression of acoustic noise in speech using spectral subtraction,” IEEE Trans. Acoustics, Speech, Signal Process., vol. ASSP-27, no. 2, pp. 113–120, Apr. 1979.

M. Berouti, R. Schwartz, and J. Makhoul. Enhancement of speech corrupted by acoustic noise. In Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), volume 4, pages 208{211, April 1979.

S. Ghael, A. M. Sayeed, and R. G. Baraniuk. Improved wavelet denoising via empirical Wiener filtering.In SPIE Tech. Conf. Wavelet Appl. Signal Proc., San Diego, July 1997.

Downloads

Published

05-05-2016

How to Cite

Vishwanath Shervegar, M., & Bhat, G. V. . (2016). Noise Estimation and Reduction in Heart Sounds Using Time Frequency Block Thresholding Method. Asian Journal of Electrical Sciences, 5(1), 26–35. https://doi.org/10.51983/ajes-2016.5.1.1968