Advertisement

Machine Vision pp 465-519 | Cite as

Preprocessing and Image Enhancement

  • Jürgen BeyererEmail author
  • Fernando Puente León
  • Christian Frese
Chapter

Abstract

The main aims of preprocessing and image enhancement are

  • to obtain visually informative images, as well as

  • to ease the subsequent signal processing and automated image evaluation steps.

The rather simple image enhancement techniques, which are covered in the following section, are mainly used for improving the visual impression of an image. Section 9.2 introduces methods which can reduce the influence of systematic perturbations caused by inhomogeneous illumination or by poor image acquisition, for example. Section 9.3 is devoted to the suppression of random noise by using linear and nonlinear filters and finally, Sec. 9.4 discusses the topic of image registration.

Keywords

Transfer Function Impulse Response Noise Reduction Image Enhancement Impulse Noise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. 1.
    Jürgen Beyerer. Analyse von Riefentexturen. PhD thesis, Universität Karlsruhe (TH), 1994.Google Scholar
  2. 2.
    Jürgen Beyerer and Fernando Puente León. Suppression of inhomogeneities in images of textured surfaces. Optical Engineering, 36(1):85–93, 1997.CrossRefGoogle Scholar
  3. 3.
    Rafael Gonzalez and RichardWoods. Digital image processing. Pearson Prentice Hall, 3rd edition, 2008.Google Scholar
  4. 4.
    Robert Haralick and Linda Shapiro. Computer and robot vision. Addison-Wesley, 1992.Google Scholar
  5. 5.
    Bernd Jähne. Digital image processing. Springer, 6th edition, 2005.Google Scholar
  6. 6.
    Anil Jain. Fundamentals of digital image processing. Prentice Hall, 1989.Google Scholar
  7. 7.
    Karl-Dirk Kammeyer and Kristian Kroschel. Digitale Signalverarbeitung – Filterung und Spektralanalyse. Vieweg+Teubner, 7th edition, 2009.Google Scholar
  8. 8.
    Jong-Sen Lee. Digital image enhancement and noise filtering by use of local statistics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2(2):165–168, 1980.Google Scholar
  9. 9.
    Tony Lindeberg. Scale space theory in computer vision. Kluwer, 1994.Google Scholar
  10. 10.
    Norbert Lins. Beschreibung von Texturen mithilfe statistischer Methoden für die Anwendung bei der Segmentierung und Qualitätskontrolle. PhD thesis, ETH Zürich, 1987.Google Scholar
  11. 11.
    Athanasios Papoulis and Unnikrishna Pillai. Probability, random variables and stochastic processes. McGraw-Hill, 4th edition, 2002.Google Scholar
  12. 12.
    Sylvain Paris and Frédo Durand. A fast approximation of the bilateral filter using a signal processing approach. In Computer Vision–ECCV 2006, pages 568–580. Springer, 2006.Google Scholar
  13. 13.
    Sylvain Paris, Pierre Kornprobst, Jack Tumblin, and Frédo Durand. Bilateral Filtering: Theory and Applications. Foundations and Trends in Computer Graphics and Vision, 4(1):1–73, 2009.CrossRefGoogle Scholar
  14. 14.
    Fernando Puente León and Holger Jäkel. Signale und Systeme. De Gruyter Oldenbourg, Berlin, 6th edition, 2015.Google Scholar
  15. 15.
    Carlo Tomasi and Roberto Manduchi. Bilateral filtering for gray and color images. In Proc. Sixth International Conference on Computer Vision (ICCV ’98), pages 839–846, 1998.Google Scholar
  16. 16.
    Friedrich Wahl. Digitale Bildsignalverarbeitung. Springer, 1989.Google Scholar
  17. 17.
    R. Wallis. An approach to the space variant restoration and enhancement of images. In Proc. Symp. on Current Mathematical Problems in Image Scenes, pages 329–340, 1976.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Jürgen Beyerer
    • 1
    Email author
  • Fernando Puente León
    • 2
  • Christian Frese
    • 3
  1. 1.Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung and The Karlsruhe Institute of TechnologyKarlsruheGermany
  2. 2.Karlsruhe Institute of TechnologyKarlsruheGermany
  3. 3.Fraunhofer-Institut für Optronik, Systemtechnik und BildauswertungKarlsruheGermany

Personalised recommendations