Skip to main content

From Scalar-Valued Images to Hypercomplex Representations and Derived Total Orderings for Morphological Operators

  • Conference paper
Mathematical Morphology and Its Application to Signal and Image Processing (ISMM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5720))

  • 753 Accesses

Abstract

In classical mathematical morphology for scalar images, the natural ordering of grey levels is used to define the erosion/dilation and the derived operators. Various operators can be sequentially applied to the resulting images always using the same ordering. In this paper we propose to consider the result of a prior transformation to define the imaginary part of a complex image, where the real part is the initial image. Then, total orderings between complex numbers allow defining subsequent morphological operations between complex pixels. In this case, the operators take into account simultaneously the information of the initial image and the processed image. In addition, the approach can be generalised to the hypercomplex representation (i.e., real quaternion) by associating to each image three different operations, for instance a directional filter. Total orderings initially introduced for colour quaternions are used to define the derived morphological transformations. Effects of these new operators are illustrated with different examples of filtering.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ablamowicz, R., Sobczyk, G.: Lectures on Clifford (Geometric) Algebras and Applications. Birkhäuser, Basel (2004)

    Book  MATH  Google Scholar 

  2. Angulo, J.: Quaternion colour representations and derived total orderings for morphological operators. In: Proc. of the CGIV 2008, pp. 417–422 (2008)

    Google Scholar 

  3. Bülow, T., Sommer, G.: Hypercomplex Signals - A Novel Extension of the Analytic Signal to the Multidimensional Case. IEEE Trans. Signal Proc. 49(11), 2844–2852 (2001)

    Article  MathSciNet  Google Scholar 

  4. Deng, T.Q., Heijmans, H.J.A.M.: Gray-scale Morphology Based on Fuzzy Logic. J. Math. Imaging Vision 16(2), 155–171 (2002)

    Article  MATH  Google Scholar 

  5. Ell, T.A., Sangwine, S.J.: Hypercomplex Wiener-Khintchine theorem with application to color image correlation. In: IEEE ICIP 2000, vol. II, pp. 792–795 (2000)

    Google Scholar 

  6. Ell, T.A., Sangwine, S.J.: Hypercomplex Fourier transform of color images. IEEE Trans. Image Proc. 16(1), 22–35 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  7. Felsberg, M., Sommer, G.: The Monogenic Signal. IEEE Trans. Signal Proc. 49(12), 3136–3144 (2001)

    Article  MathSciNet  Google Scholar 

  8. Felsberg, M., Sommer, G.: The monogenic scale-space: A unifying approach to phase-based image processing in scale-space. J. Math. Imaging Vision 21, 5–26 (2004)

    Article  MathSciNet  Google Scholar 

  9. Heijmans, H.J.A.M.: Morphological Image Operators. Academic Press, Boston (1994)

    MATH  Google Scholar 

  10. Heijmans, H.J.A.M., Keshet, R.: Inf-Semilattice Approach to Self-Dual Morphology. J. Math. Imaging Vision 17(1), 55–80 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  11. Matheron, G.: Les treillis compacts. Technical Report - Paris School of Mines, N-23/90/G (1990)

    Google Scholar 

  12. Meyer, F.: Constrast features extraction. In: Chermant (ed.) Quantitative Analysis of Microstructures in Materials Science, Biology and Medecine, pp. 374–380. Riederer Verlag (1977)

    Google Scholar 

  13. Meyer, F., Angulo, J.: Micro-viscous morphological operators. In: Mathematical Morphology and its applications to Signal and Image Processing (ISMM 2007), pp. 165–176 (2007)

    Google Scholar 

  14. Sangwine, S.J., Ell, T.A.: Mathematical approaches to linear vector filtering of colour images. In: Proc. CGIV 2002, pp. 348–351 (2002)

    Google Scholar 

  15. Serra, J.: Image Analysis and Mathematical Morphology, vol. I. Academic Press, London (1982)

    MATH  Google Scholar 

  16. Serra, J.: Image Analysis and Mathematical Morphology. Theoretical Advances, vol. II. Academic Press, London (1988)

    Google Scholar 

  17. Serra, J.: Anamorphoses and Function Lattices (Multivalued Morphology). In: Dougherty (ed.) Mathematical Morphology in Image Processing, pp. 483–523. Marcel-Dekker, New York (1992)

    Google Scholar 

  18. Shi, L., Funt, B.: Quaternion color texture segmentation. Computer Vision and Image Understanding 107(1-2), 88–96 (2007)

    Article  Google Scholar 

  19. Zang, D., Sommer, G.: Signal modeling for two-dimensional image structures. J. Vis. Commun. Image R. 18, 81–99 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Angulo, J. (2009). From Scalar-Valued Images to Hypercomplex Representations and Derived Total Orderings for Morphological Operators. In: Wilkinson, M.H.F., Roerdink, J.B.T.M. (eds) Mathematical Morphology and Its Application to Signal and Image Processing. ISMM 2009. Lecture Notes in Computer Science, vol 5720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03613-2_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03613-2_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03612-5

  • Online ISBN: 978-3-642-03613-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics