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Modelling Line and Edge Features Using Higher-Order Riesz Transforms

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8192))

Abstract

The 2D-complex Riesz transform is an extension of the Hilbert transform to images. It can be used to model local image structure as a superposition of sinusoids, and to construct 2D steerable wavelets. In this paper we propose to model local image structure as the superposition of a 2D steerable wavelet at multiple amplitudes and orientations. These parameters are estimated by applying recent developments in super-resolution theory. Using 2D steerable wavelets corresponding to line or edge segments then allows for the underlying structure of image features such as junctions and edges to be determined.

The first author is supported by JCU and CSIRO scholarships. This research is part of the CSIRO Transformational Biology Capability Platform.

The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02895-8_64

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References

  1. Newell, A., Griffin, L.: Natural Image Character Recognition Using Oriented Basic Image Features. In: Proc. Int. Conf. Digital Image Computing Techniques and Applications, pp. 191–196 (December 2011)

    Google Scholar 

  2. Felsberg, M., Sommer, G.: The monogenic signal. IEEE Trans. Signal Process. 49(12), 3136–3144 (2001)

    Article  MathSciNet  Google Scholar 

  3. Zang, D., Sommer, G.: The Monogenic Curvature Scale-Space. In: Reulke, R., Eckardt, U., Flach, B., Knauer, U., Polthier, K. (eds.) IWCIA 2006. LNCS, vol. 4040, pp. 320–332. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  4. Wietzke, L., Sommer, G.: The Signal Multi-Vector. J. Math. Imaging and Vision 37(2), 132–150 (2010)

    Article  MathSciNet  Google Scholar 

  5. Fleischmann, O., Wietzke, L., Sommer, G.: Image Analysis by Conformal Embedding. J. Math. Imaging and Vision 40(3), 305–325 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  6. Unser, M., Van De Ville, D.: Wavelet steerability and the higher-order Riesz transform. IEEE Trans. Image Process. 19(3), 636–652 (2010)

    Article  MathSciNet  Google Scholar 

  7. Unser, M., Chenouard, N.: A unifying parametric framework for 2D steerable wavelet transforms. SIAM J. Imaging Sci. 6(1), 102–135 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  8. Candes, E., Fernandez-Granda, C.: Towards a mathematical theory of super-resolution. arXiv preprint arXiv:1203.5871 (2012)

    Google Scholar 

  9. Candes, E., Fernandez-Granda, C.: Super-resolution from noisy data. arXiv preprint arXiv:1211.0290 (2012)

    Google Scholar 

  10. Marchant, R., Jackway, P.: Feature detection from the maximal response to a spherical quadrature filter set. In: Proc. Int. Conf. Digital Image Computing Techniques and Applications (December 2012)

    Google Scholar 

  11. Freeman, W.T., Adelson, E.H.: The design and use of steerable filters. IEEE Trans. Pattern Anal. Mach. Intell. 13(9), 891–906 (1991)

    Article  Google Scholar 

  12. Mühlich, M., Friedrich, D., Aach, T.: Design and Implementation of Multisteerable Matched Filters. IEEE Trans. Pattern Anal. Mach. Intell. 34(2), 279–291 (2012)

    Article  Google Scholar 

  13. Ward, J., Chaudhury, K., Unser, M.: Decay properties of Riesz transforms and steerable wavelets. arXiv preprint arXiv:1301.2525 (2013)

    Google Scholar 

  14. Boukerroui, D., Noble, J., Brady, M.: On the Choice of Band-Pass Quadrature Filters. J. Math. Imaging and Vision 21(1), 53–80 (2004)

    Article  MathSciNet  Google Scholar 

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Marchant, R., Jackway, P. (2013). Modelling Line and Edge Features Using Higher-Order Riesz Transforms. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2013. Lecture Notes in Computer Science, vol 8192. Springer, Cham. https://doi.org/10.1007/978-3-319-02895-8_39

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  • DOI: https://doi.org/10.1007/978-3-319-02895-8_39

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02894-1

  • Online ISBN: 978-3-319-02895-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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