Spectral decomposition and de‐noising via time‐frequency and space‐wavenumber reassignment

References

1. AugerF. and FlandrinP.1995. Improving the readability of time‐frequency and time‐scale representations by the reassignment method. IEEE Transactions on Signal Processing43, 1068–1089.
   [Google Scholar]
2. BarnesA.E.2007a. A tutorial on complex seismic trace analysis. Geophysics72, W33–W43.
   [Google Scholar]
3. BarnesA.E.2007b. A tutorial on complex seismic trace analysis. Geophysics72, W33–W43.
   [Google Scholar]
4. BeckA. and TeboulleM.2009. A fast iterative shrinkage‐thresholding algorithm for linear inverse problems. SIAM Journal on Imaging Sciences2, 183–202.
   [Google Scholar]
5. BonarD.C. and SacchiM.D.2010. Complex spectral decomposition via inversion strategies. SEG Technical Program Expanded Abstracts29, 1408–1412.
   [Google Scholar]
6. BonarD. and SacchiM.2013. Spectral decomposition with f‐x‐y preconditioning. Geophysical Prospecting61, 152–165.
   [Google Scholar]
7. CanalesL.L.1984. Random noise reduction. 54th Annual International Meeting, SEG, Expanded Abstracts, Session, S10.1.
   [Google Scholar]
8. CastagnaJ.P., SunS. and SiegfriedR.W.2003. Instantaneous spectral analysis: De‐ tection of low‐frequency shadows associated with hydrocarbons. The Leading Edge22, 120–127.
   [Google Scholar]
9. ChopraS., CastagnaJ. and PortniaguineO.2006. Thin‐bed reflectivity inversion. SEG Technical Program Expanded Abstracts25, 2057–2061.
   [Google Scholar]
10. ClaasenT. and MecklenbraukerW.F.G.1980. The Wigner distribution – A tool for time frequency signal analysis. Part II: Discrete‐time signals. Philips Journal of Research35, 276–300.
    [Google Scholar]
11. ElbothT., Vik PresterudI. and HermansenD.2010. Time‐frequency seismic data denoising. Geophysical Prospecting58, 441–453.
    [Google Scholar]
12. FitzK. and HakenL.2002. On the use of time‐frequency reassignment in additive sound modeling. Journal of the Audio Engineering Society5, 1–25.
    [Google Scholar]
13. FlandrinP., AugerF. and Chassande‐MottinE.2003. Time‐frequency reassignment: From principles to algorithms. In: Applications in Time‐Frequency Signal Processing, 179–203.
    [Google Scholar]
14. FulopS.A.2010. Accuracy of formant measurement for synthesized vowels using the reassigned spectrogram and comparison with linear prediction. The Journal of the Acoustical Society of America127, 2114–7.
    [Google Scholar]
15. FulopS.A. and FitzK.2006. Algorithms for computing the time‐corrected instantaneous frequency (reassigned) spectrogram, with applications. The Journal of the Acoustical Society of America119, 360.
    [Google Scholar]
16. GaborD.1946. Theory of communication. Part 1: The analysis of information. Journal of the Institution of Electrical Engineers93, 429–445.
    [Google Scholar]
17. HainsworthS.W., MacleodM.D. and WolfeP.J.2001. Analysis of reassigned spectro‐ grams for musical transcription. Proc DAFX98 Digital Audio Effects Workshop, Citeseer, 23–26.
    [Google Scholar]
18. HanJ. and van der BaanM.2013. Empirical mode decomposition for seismic time frequency analysis. Geophysics78, O9–O19.
    [Google Scholar]
19. HanL., BonarD.C. and SacchiM.D.2012. Seismic denoising by time‐frequency reassignment. CSEG Expanded Abstracts.
    [Google Scholar]
20. HerrmannF.J. and LiX.2012. Efficient least‐squares imaging with sparsity promotion and compressive sensing. Geophysical Prospecting60, 696–712.
    [Google Scholar]
21. HuangN.E. and ShenS.S.2005. Hilbert‐Huang Transform and its Applications. World Scientific Publishing Co. Pte. Ltd., Volume 5 of Interdisciplinary Mathematical Sciences.
    [Google Scholar]
22. HyslopC.W. and DialloM.S.2010. Energy Reassignment of an Image for Improved Picking of Velocity Dispersion Curves. 72nd EAGE Conference & Exhibition incorporating SPE EUROPEC, 14–17.
    [Google Scholar]
23. KahooA.R. and SiahkoohiH.R.2009. Random noise suppression from seismic data using time‐frequency peak filtering. 71st EAGE Conference & Exhibition, 1059–1063.
    [Google Scholar]
24. KoderaK., De VilledaryC. and GendrinR.1976. A new method for the numerical analysis of non‐stationary signals. Physics of the Earth and Planetary Interiors12, 142–150.
    [Google Scholar]
25. KoderaK., GendrinR. and De VilledaryC.1978. Analysis of time‐varying signals with small BT values: Acoustics, Speech and Signal Processing. IEEE Transactions on Acoustics, Speech and Signal Processing26, 64–76.
    [Google Scholar]
26. LiY., ZhengX. and ZhangY.2011. High‐frequency anomalies in carbonate reservoir characterization using spectral decomposition. Geophysics76, V47–V57.
    [Google Scholar]
27. MaY. and MargraveG.F.2008. Seismic depth imaging with the Gabor transform. Geophysics73, S91–S97.
    [Google Scholar]
28. MallatS.1989. A theory for multiresolution signal decomposition: the wavelet represen‐ tation: Pattern Analysis and Machine Intelligence. IEEE Transactions on Pattern Analysis and Machine Intelligence11, 674–693.
    [Google Scholar]
29. MallatS. and ZhangZ.1993. Matching pursuits with time‐frequency dictionaries: Signal Processing. IEEE Transactions on Signal Processing41, 3397–3415.
    [Google Scholar]
30. MargraveG.F., LamoureuxM.P. and HenleyD.C.2011. Gabor deconvolution: Es‐ timating reflectivity by nonstationary deconvolution of seismic data. Geophysics76, W15–W30.
    [Google Scholar]
31. OdegardJ. and BaraniukR.1998. Instantaneous frequency estimation using the reassignment method. Proceedings of the SEG Meeting, 1941–1944.
    [Google Scholar]
32. PartykaG., GridleyJ. and LopezJ.1999. Interpretational applications of spectral de‐ composition in reservoir characterization. The Leading Edge18, 353–360.
    [Google Scholar]
33. PedersenH.A., MarsJ.I. and AmblardP.O.2003. Improving surface‐wave group velocity measurements by energy reassignment. Geophysics68, 677–684.
    [Google Scholar]
34. PinnegarC.R. and MansinhaL.2003. The S‐transform with windows of arbitrary and varying shape. Geophysics68, 381–385.
    [Google Scholar]
35. PlanteF., MeyerG. and AinsworthW.A.1998. Improvement of speech spectrogram accu‐ racy by the method of reassignment. IEEE Transactions of Speech and Audio Processing6, 282–287.
    [Google Scholar]
36. PortniaguineO. and CastagnaJ.2004. Inverse spectral decomposition. SEG Technical Program Expanded Abstracts23, 1786–1789.
    [Google Scholar]
37. PoularikasA.D.2010. Transforms and Applications Handbook. Third edition. CRC Press 2010, Volume 43 of the Electrical Engineering Handbook Series.
    [Google Scholar]
38. PuryearC.I., PortniaguineO.N., CobosC.M. and CastagnaJ.P.2012. Constrained least‐squares spectral analysis: Application to seismic data. Geophysics77, V143–V167.
    [Google Scholar]
39. SacchiM.D., KaplanS. and NaghizadehM.2009. F‐X Gabor seismic data reconstruction. 71st Annual International Conference and Exhibition.
    [Google Scholar]
40. SinhaS., RouthP.S., AnnoP.D. and CastagnaJ.P.2005. Spectral decomposition of seismic data with continuous‐wavelet transform. Geophysics70, P19–P25.
    [Google Scholar]
41. Vera RodriguezI., BonarD. and SacchiM.D.2012. Microseismic data denoising using a 3C group sparsity constrained time‐frequency transform. Geophysics77, V21–V29.
    [Google Scholar]
42. WangY.2007. Seismic time‐frequency spectral decomposition by matching pursuit. Geophysics72, V13–V20.
    [Google Scholar]
43. WangY.2010. Multichannel matching pursuit for seismic trace decomposition. Geophysics75, V61–V66.
    [Google Scholar]
44. WangJ. and SacchiM.D.2007. High‐resolution wave‐equation amplitude‐variation‐with‐ray‐parameter (AVP) imaging with sparseness constraints. Geophysics72, S11–S18.
    [Google Scholar]
45. YooS. and GibsonR.L.2005. Frequency dependent AVO analysis after target oriented stretch correction. SEG Technical Program Expanded Abstracts24, 293–296.
    [Google Scholar]