SpringerLink
Log in

Locally adaptive fuzzy image enhancement

  • Conference paper
  • First Online:
Computational Intelligence Theory and Applications (Fuzzy Days 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1226))

Included in the following conference series:

Abstract

In recent years, some researchers have applied the concept of fuzziness to develop new enhancement algorithms. The global fuzzy image enhancement methods, however, fail occasionally to achieve satisfactory results. In this work, we introduce a locally adaptive version of two existing fuzzy image enhancement algorithms to overcome this problem.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Banks, S., Signal Processing, Image Processing and Pattern Recognition, Prentice Hall International, 1990.

    Google Scholar 

  2. Gonzalez, R. C., Woods, R. E., Digital Image Processing, Addison-Wesley Publishing Group, second edition, 1992.

    Google Scholar 

  3. King, R.A., Pal, S. K., Image Enhancement Using Smoothing with Fuzzy Sets, IEEE Transactions on Systems, Man and Cybernetics, vol. SMC-11, no. 7, pp. 494–501, July 1981.

    Google Scholar 

  4. King, R. A., Pal, S. K., On edge detection of X-ray images using fuzzy sets, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-5, No. 1, pp. 69–77, 1983.

    Google Scholar 

  5. Pal, S. K., Fuzziness, Image Information and Scene Analysis. In: Yager, R., Zadeh, L. A.: An Introduction to Fuzzy Logic Applications in Intelligent Systems, pp. 147–183, Kluwer Academic Publishers, 1992.

    Google Scholar 

  6. Ross, T. J., Fuzzy Logic with Engineering Applications, McGraw-Hill, USA, 1995.

    Google Scholar 

  7. Tizhoosh, H. R., Fochem, M., Image Enhancement with Fuzzy Histogram Hyperbolization, Proceedings of EUFIT'95, vol. 3, pp. 1695–1698, Aachen, Germany, 1995.

    Google Scholar 

  8. Zadeh, L. A., Fuzzy Sets, Information and Control 8, p. 338–353, 1965.

    Google Scholar 

  9. Zadeh, L. A., A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges, J. Cybern., vol. 2, no. 2, pp. 4–34, 1972.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute for Measurement Technology and Electronics, Otto-von-Guericke-University Magdeburg, P.O. Box 4120, D-39016, Magdeburg, Germany

    H. R. Tizhoosh, G. Krell & B. Michaelis

Authors
  1. H. R. Tizhoosh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. G. Krell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B. Michaelis
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Bernd Reusch

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tizhoosh, H.R., Krell, G., Michaelis, B. (1997). Locally adaptive fuzzy image enhancement. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_118

Download citation

  • DOI: https://doi.org/10.1007/3-540-62868-1_118

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62868-2

  • Online ISBN: 978-3-540-69031-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation