Transients Detection in the Time-Scale Domain

  • V. Bruni
  • D. Vitulano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5099)


In this paper a novel model for transients detection in piecewise stationary signals is presented. A hybrid representation is assumed for the signal and the different behavior of each component (stationary, transient and stochastic) in the time-scale plane is exploited. Experimental results on both shape contours, described by a differential chain code, and audio signals show the generality of the proposed model.


Transients chain code shape analysis audio signal wavelets 


  1. 1.
    Bello, J.P., Daudet, L., Abdallah, S., Duxbury, C., Davies, M., Sandler, M.B.: A Tutorial on Onset Detection in Music Signals. IEEE Trans. on Speech and Audio Processing 13(5), 1035–1047 (2005)CrossRefGoogle Scholar
  2. 2.
    Bruni, V., Piccoli, B., Vitulano, D.: Wavelet time-scale Dependencies for Signal and Image Compression. In: Pan, Y., Chen, D.-x., Guo, M., Cao, J., Dongarra, J. (eds.) ISPA 2005. LNCS, vol. 3758, pp. 105–110. Springer, Heidelberg (2005)Google Scholar
  3. 3.
    Bruni, V., Vitulano, D.: Wavelet based Signal Denoising via Simple Singularities Approximation. Signal Processing 86, 859–876 (2006)zbMATHCrossRefGoogle Scholar
  4. 4.
    Daudet, L.: A Review on Techniques for the Extraction of Transients in Musical Signals. Computer Music Modeling and Retrieval, 219–232 (2005)Google Scholar
  5. 5.
    Daudet, L.: Sparse and Structured Decompositions of Signals with the Molecular Matching Pursuit. IEEE Trans. on Audio, Speech and Language Processing 14(5) (2006)Google Scholar
  6. 6.
    Daudet, L., Torresani, B.: Hybrid representations for audiophonic signal encoding. Signal Processing, Special issue on Image and Video Coding Beyond Standards 82(11), 1595–1617 (2002)zbMATHGoogle Scholar
  7. 7.
    Duxbury, C., Davies, M.E., Sandler, M.B.: Separation Of Transient Information In Musical Audio Using Multiresolution Analysis Techniques. In: 4th Int. Workshop on Digital Audio Effects, DAFX 2001, Limerick (2001)Google Scholar
  8. 8.
    Duxbury, C., Chetry, N., Sandler, M., Davies, M.E.: An efficient two-stage implementation of Harmonic Matching Pursuit. In: Proc. of EUSIPCO 2004(2004)Google Scholar
  9. 9.
    Gonzales, R.C., Woods, R.E.: Digital Image Processing. Prentice-Hall, Englewood Cliffs (2002)Google Scholar
  10. 10.
    Grinboval, R., Bacry, E.: Harmonic Decomposition of Audio Signals with Matching Pursuit. IEEE Trans. on Signal Processing 51(1) (January 2005)Google Scholar
  11. 11.
    Mallat, S., Hwang, W.L.: Singularity Detection and Processing with Wavelet. IEEE Trans. on Information Theory 38, 617–643 (1992)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Mallat, S.: A Wavelet Tour of Signal Processing. Academic Press, London (1999)zbMATHGoogle Scholar
  13. 13.
    Molla, S., Torresani, B.: Determining local transientness in audio signals. IEEE Signal Processing Letters 11(7), 625–628 (2004)zbMATHCrossRefGoogle Scholar
  14. 14.
    Tantibundhit, C., Boston, J.R., Li, C.C., Durrant, J.D., Shaiman, S., Kovacyk, K., El-Jaraoudi, A.: Speech Enhancement using Transient Speech Components. In: Proc. of IEEE ICASSP 2006 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • V. Bruni
    • 1
  • D. Vitulano
    • 1
  1. 1.Istituto per le Applicazioni del Calcolo - C.N.R.RomeItaly

Personalised recommendations