Skip to main content
Log in

Geometric Separation in \(\mathbb {R}^3\)

  • Published:
Journal of Fourier Analysis and Applications Aims and scope Submit manuscript

Abstract

The geometric separation problem, initially posed by Donoho and Kutyniok (Commun Pure Appl Math 66:1–47, 2013), aims to separate a distribution containing a non-trivial superposition of point and curvilinear singularities into its distinct geometric constituents. The solution proposed in Donoho and Kutyniok  (2013) considers expansions with respect to a combined wavelet-curvelet dictionary and applies an \(\ell ^1\)-norm minimization over the expansion coefficients to achieve separation asymptotically at fine scales. However, the original proof of this result uses a heavy machinery relying on sparse representations of Fourier integral operators which does not extend directly to the 3D setting. In this paper, we extend the geometric separation result to the 3D setting using a novel and simpler argument which relies in part on techniques developed by the authors for the shearlet-based analysis of curvilinear edges. Our new result also yields a significantly simpler proof of the original 2D geometric separation problem and extends a prior result by the authors which was limited to piecewise linear singularities.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. Here we ignore that boundary elements corresponding to \(\ell = \pm 2^j\) are slightly modified as it is irrelevant for our arguments.

References

  1. Candès, E.J., Donoho, D.L.: Ridgelets: the key to high dimensional intermittency? Philos. Trans. R. Soc. Lond. A 357, 2495–2509 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  2. Candès, E.J., Donoho, D.L.: New tight frames of curvelets and optimal representations of objects with C 2 singularities. Commun. Pure Appl. Math. 56, 219–266 (2004)

    Article  MATH  Google Scholar 

  3. Candès, E.J., Romberg, J.K., Tao, T.: Stable signal recovery from incomplete and inaccurate measurements. Commun. Pure Appl. Math. 59, 1207–1223 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  4. Chen, S.S., Donoho, D.L., Saunders, M.A.: Atomic decomposition by basis pursuit. SIAM Rev. 43, 129–159 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  5. Coifman, R. R., Wickerhauser. M. V.: Wavelets and adapted waveform analysis. A toolkit for signal processing and numerical analysis, Different perspectives on wavelets (San Antonio, TX, 1993), 119–153. In: Proceedings of Symposia in Applied Mathematics, Vol 47, American Mathematical Society, Providence, RI, (1993)

  6. Donoho, D.L.: For most large underdetermined systems of linear equations the minimal \(\ell ^1\)-norm solution is also the sparsest solution. Commun. Pure Appl. Math. 59, 97–829 (2006)

    MathSciNet  Google Scholar 

  7. Donoho, D., Kutyniok, G.: Microlocal analysis of the geometric separation problem. Commun. Pure Appl. Math. 66, 1–47 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  8. Easley, G.R., Labate, D., Lim, W.: Sparse directional image representations using the discrete shearlet transform. Appl. Comput. Harmon. Anal. 25, 25–46 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  9. Gribonval, R., Bacry, E.: Harmonic decomposition of audio signals with matching pursuit. IEEE Trans. Signal Proc. 51, 1001–111 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  10. Guo, K., Labate, D.: Optimally sparse multidimensional representation using shearlets. SIAM J. Math. Anal. 39, 298–318 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  11. Guo, K., Labate, D.: Characterization and analysis of edges using the continuous shearlet transform. SIAM J. Imaging Sci. 2, 959–986 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  12. Guo, K., Labate, D.: Analysis and detection of surface discontinuities using the 3D continuous shearlet transform. Appl. Comput. Harmon. Anal. 30, 231–242 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  13. Guo, K., Labate, D.: Optimally sparse representations of 3D data with C 2 surface singularities using Parseval frames of shearlets. SIAM J. Math. Anal. 44, 851–886 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  14. Guo, K., Labate, D.: Characterization of piecewise smooth surfaces using the 3D continuous shearlet transform. J. Fourier Anal. Appl. 18, 488–516 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  15. Guo, K., Labate, D.: The construction of smooth Parseval frames of shearlets. Math. Model. Nat. Phenom. 8, 82–105 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  16. Guo, K., Labate, D.: Geometric separation of singularities using combined multiscale dictionaries. J. Fourier Anal. Appl. 21, 667–693 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  17. Guo, K., Labate, D.: Microlocal analysis of edge flatness through directional multiscale representations. Adv. Comput. Math. 43, 295–318 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  18. Guo, K., Labate, D., Lim, W.: Edge analysis and identification using the continuous shearlet transform. Appl. Comput. Harmon. Anal. 27, 24–46 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  19. Guo, K., Houska, R., Labate, D.: Microlocal analysis of singularities from directional multiscale representations. In: Approximation Theory XIV (San Antonio, pp. 173–196). Springer, Charm. Proceedings in Mathematics & Statistics 83, 2014 (2013)

  20. Hernandez, E., Weiss, G.: A First Course on Wavelets. CRC Press, Boca Raton, FL (1996)

    Book  MATH  Google Scholar 

  21. King, E., Kutyniok, G., Zhuang, X.: Analysis of inpainting via clustered sparsity and microlocal analysis. J. Math. Imaging Vis. 48(2), 205–234 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  22. Kutyniok, G.: Geometric separation by single-pass alternating thresholding. Appl. Comput. Harmon. Anal. 36, 23–50 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  23. Kutyniok, G., Labate, D.: Resolution of the wavefront set using continuous shearlets. Trans. Am. Math. Soc. 361, 2719–2754 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  24. Kutyniok, G., Petersen, P.: Classification of edges using compactly supported shearlets. Appl. Comput. Harmon. Anal. 42, 245–293 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  25. Kutyniok, G., Lemvig, J., Lim, W.-Q.: Optimally sparse approximations of 3D functions by compactly supported shearlet frames. SIAM J. Math. Anal. 44, 2962–3017 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  26. Kutyniok, G., Shahram, M., Zhuang, X.: ShearLab: a rational design of a digital parabolic scaling. SIAM J. Imaging Sci. 5, 1291–1332 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  27. Labate, D., Lim, W., Kutyniok, G., Weiss, G.: Sparse multidimensional representation using shearlets. SPIE Proc. 5914, 254–262 (2005)

    Google Scholar 

  28. Mallat, S.G., Zhang, Z.: Matching pursuits with time-frequency dictionaries. IEEE Trans. Signal Proc. 41, 3397–3415 (1993)

    Article  MATH  Google Scholar 

  29. Meyer, F.G., Averbuch, A., Coifman, R.R.: Multi-layered image representation: application to image compression. IEEE Trans. Image Process. 11, 1072–1080 (2002)

    Article  MathSciNet  Google Scholar 

  30. Starck, J.-L., Nguyen, M., Murtagh, F.: Wavelets and curvelets for image deconvolution: a combined approach. Signal Process. 83, 2279–2283 (2003)

    Article  MATH  Google Scholar 

  31. Starck, J.-L., Elad, M., Donoho, D.L.: Redundant multiscale transforms and their application for morphological component analysis. Adv. Imaging Electron Phys. 132, 287–348 (2004)

    Article  Google Scholar 

  32. Starck, J.-L., Elad, M., Donoho, D.L.: Image decomposition via the combination of sparse representation and a variational approach. IEEE Trans. Image Process. 14, 1570–1582 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  33. Stein, E.M.: Harmonic Analysis: Real-Variable Methods, Orthogonality, and Oscillatory Integrals. Princeton University Press, Princeton (1993)

    MATH  Google Scholar 

  34. Strichartz, R.S.: A guide to distribution theory and Fourier transforms. World Scientific Publishing, Singapore (2003)

    Book  MATH  Google Scholar 

  35. Teschke, G.: Multi-frame representations in linear inverse problems with mixed multi-constraints. Appl. Comput. Harmon. Anal. 22, 43–60 (2007)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

DL acknowledges support from NSF grant DMS 1720487, GEAR 113491 and by a grant from the Simon Foundation (422488).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Demetrio Labate.

Additional information

Communicated by Gitta Kutyniok.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guo, K., Labate, D. Geometric Separation in \(\mathbb {R}^3\). J Fourier Anal Appl 25, 108–130 (2019). https://doi.org/10.1007/s00041-017-9569-z

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00041-017-9569-z

Keywords

Mathematics Subject Classification

Navigation