Sound texture synthesis with hidden markov tree modelsin the wavelet domain

Proceedings of the 7th Sound and Music Computing Conference, SMC 2010

Volumn , Issue , 2010, Pages 60-

  Kersten, Stefan ^a   Purwins, Hendrik ^a  

^a UNIVERSITAT POMPEU FABRA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER GRAPHICS; TEXTURES; WAVELET DECOMPOSITION;

ENVIRONMENTAL SOUNDS; HIDDEN MARKOV TREE; IMAGE TEXTURE ANALYSIS; INFORMAL LISTENING; PARAMETRIC MODELING; TEXTURE SYNTHESIS; TIME-DOMAIN SIGNAL; WAVELET COEFFICIENTS;

IMAGE SEGMENTATION;

EID: 84905180052     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. R. M. Schafer, The Soundscape: Our Sonic Environment and the Tuning of the World. Destiny Books, 1994.
2. N. Saint-Arnaud, Classification of Sound Textures. Master thesis, Massachusetts Institute of Technology, 1995.
3. J. H. McDermott, A. J. Oxenham, and E. P. Simon-celli, Sound texture synthesis via filter statistics, in Proceedings IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, (New Paltz, NY), Oct. 2009.
4. S. Dubnov, Z. Bar-Joseph, R. El-Yaniv, D. Lischinski, and M. Werman, Synthesizing sound textures through wavelet tree learning, Computer Graphics and Applications, IEEE, vol. 22, pp. 38-48, July 2002.
5. D. ORegan and A. Kokaram, Multi-Resolution sound texture synthesis using the Dual-Tree complex wavelet transform, in Proc. 2007 European Signal Processing Conference (EUSIPCO), 2007.
6. A. Kokaram and D. O'Regan, Wavelet based high resolution sound texture synthesis, in Proc. 31st International Conference: New Directions in High Resolution Audio, June 2007.
7. D. D. Po and M. N. Do, Directional multiscale modeling of images using the contourlet transform, IEEE Transactions on Image Processing, vol. 15, no. 6, p. 1610-1620, 2006.
8. M. Crouse, R. Nowak, and R. Baraniuk, Wavelet-based statistical signal processing using hidden markov models, Signal Processing, IEEE Transactions on, vol. 46, no. 4, pp. 886-902, 1998.
9. G. Strobl, G. Eckel, D. Rocchesso, and S. Le Grazie, Sound texture modeling: A survey, 2006.
10. A. Efros and T. K. Leung, Texture synthesis by Non-Parametric sampling, in Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2, p. 1033, IEEE Computer Society, 1999.
11. Willsky, Multiresolution markov models for signal and image processing, Proceedings of the IEEE, vol. 90, no. 8, pp. 1396-1458, 2002.
12. H. Choi, J. Romberg, R. Baraniuk, and N. Kingsbury, Hidden markov tree modeling of complex wavelet transforms, in Acoustics, Speech, and Signal Processing, 2000. ICASSP'00. Proceedings. 2000 IEEE International Conference on, vol. 1, pp. 133-136 vol.1, 2000.
13. J. Durand, P. Goncalves, and Y. Guedon, Computational methods for hidden markov tree models-an application to wavelet trees, Signal Processing, IEEE Transactions on, vol. 52, no. 9, pp. 2551-2560, 2004.
14. D. H. Milone, L. E. D. Persia, and M. E. Torres, De-noising and recognition using hidden markov models with observation distributions modeled by hidden markov trees, Pattern Recogn., vol. 43, no. 4, pp. 1577-1589, 2010.
15. G. Fan and X. G. Xia, Wavelet-based texture analysis and synthesis using hidden markov models, IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 50, no. 1, p. 106-120, 2003.
16. Daubechies, Orthonormal bases of compactly supported wavelets, Communications on Pure and Applied Mathematics, vol. 41, no. 7, pp. 909-996, 1988.
17. G. Fan and X. G. Xia, Improved hidden markov models in the wavelet-domain, IEEE TRANS SIGNAL PROCESS, vol. 49, no. 1, p. 115-120, 2001.
18. M. Bishop, Pattern Recognition and Machine Learning. Information Science and Statistics, New York, NY, USA: Springer, 2006.
19. H. Lucke, Which stochastic models allow Baum-Welch training?, Signal Processing, IEEE Transactions on, vol. 44, no. 11, pp. 2746-2756, 1996.