Aspects of Image Processing for Multimedia Applications

Part of the NATO ASI Series book series (ASHT, volume 30)


The use of multimedia systems can greatly improve the communication of users with complex systems through the use of additional information representations. Media used in such systems often include still and moving images. These generate large data volumes which make image compression techniques are sensitive to noise in images. In this paper noise cleaning methods are considered. A method which can be used to eliminate the shortcomings of a promising new method is discussed. Possibilities for parallelising the compute intensive computations are outlined.


Video Clip Median Filter Image Compression Noisy Image Multimedia System 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Pratt, W.K. (1991) Digital image processing, John Wiley & Sons, Inc, New YorkzbMATHGoogle Scholar
  2. 2.
    Rohwer, C.H. (1989) Idempotent one-sided approximation of median smoothers, Journal of Approximation Theory, Vol. 58, No. 2MathSciNetCrossRefGoogle Scholar
  3. 3.
    Rohwer, C.H. and Toerien L.M.(1991) Locally monotone robust approximation of sequences, Journal of Computational and Applied Mathematics Vol. 36, 399–408MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Lin, H. and Alan, N. (1988) Adaptive-length median filters for image processing, IEEE International Symposium on Circuits and Systems, 2557–2560Google Scholar
  5. 5.
    Gabbouj, M., Coyle, E. J., Gallagher, N. (1992) Overview of median and stack filtering, Journal of Circuits and Systems, Vol. 11, No. 1, 7–45zbMATHGoogle Scholar
  6. 6.
    Tukey, J.W. (1971) Exploratory data analysis, Addison-Wesley, Reading, MAGoogle Scholar
  7. 7.
    Falkemeier, G. and Joubert, G. R. (1995) Parallel image compression with JPEG for multimedia applications in J.J. Dongara, L. Grandinetti, G.R. Joubert, J. Kowalik (eds.), High Performance Computing: Technology, Methods and Applications, Elsevier Science, AmsterdamGoogle Scholar
  8. 8.
    Falkemeier, G., Fitschen, J. and Joubert, G. R. (1996) Parallel fractal & JPEG image compression, in E. D’Hollander, G.R. Joubert, F. Peters, D. Trystram (eds.), Parallel Computing: State-of-the-art and Perspectives, Elsevier Science, AmsterdamGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  1. 1.Department of Computer ScienceTechnical University of ClausthalClausthalGermany

Personalised recommendations