Case Studies

  • Robert King
  • Majid Ahmadi
  • Raouf Gorgui-Naguib
  • Alan Kwabwe
  • Mahmood Azimi-Sadjadi

Abstract

This chapter describes some case studies that demonstrate the techniques discussed in Chapter 11. The scope, however, is restricted to applications of linear digital filters only. In any case study, digital filtering forms only a part, nevertheless an important part, of the processes which must be applied to the image in order to achieve the desired objective; as such it is described within the context of the application.

Keywords

Digital Filter Partial Information Template Match Image Restoration Wiener Filter 
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.

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References

  1. 1.
    R. W. Schafer, R. M. Mersereau, and M. A. Richards, Constrained iterative restoration algorithms, Proc. IEEE 69, 432–450 (1981).CrossRefGoogle Scholar
  2. 2.
    D. C. Youla and H. Webb, Image reconstruction by the method of convex projections; Part 1: Theory, IEEE Trans. Med. Imaging MI-1, 81–94 (1982).CrossRefGoogle Scholar
  3. 3.
    M. I. Sezan and H. Stark, Image restoration by the method of convex projections; Part 2: Applications and numerical results, IEEE Trans. Med. Imaging MI-1, 95–101 (1982).CrossRefGoogle Scholar
  4. 4.
    M. R. Civanlar and H. J. Trussell, Digital signal restoration using fuzzy sets, IEEE Trans. Acoust., Speech, Signal Process. ASSP-34, 919–936 (1986).CrossRefGoogle Scholar
  5. 5.
    R. King, K. Singarajah, and A. S. Kwabwe, A Hybrid Technique to Restore the Phase and Magnitude of Noisy Linearly Degraded Images, IEEE International Conference on Acoustics, Speech and Signal Processing, Boston (1983).Google Scholar
  6. 6.
    R. W. Gerchberg, Super-resolution through error energy reduction, Opt. Acta 21, 709–720 (1974).CrossRefGoogle Scholar
  7. 7.
    A. S. Kwabwe, Image Reconstruction from Incomplete Information, PhD Thesis, Imperial College, University of London (1984).Google Scholar
  8. 8.
    D. E. Dudgeon and R. M. Mersereau, Multidimensional Digital Signal Processing, Prentice-Hall, Englewood Cliffs, NJ (1984).MATHGoogle Scholar
  9. 9.
    S. I. Sayegh, Y.-L. Kok, and J-H. Hong, An algorithm to find two-dimensional signals with specified zero crossings, IEEE Trans. Acoust., Speech, Signal Process. ASSP-35, 107–111 (1987).CrossRefGoogle Scholar
  10. 10.
    A. V. Oppenheim and J. S. Lim, The importance of phase in signals, Proc. IEEE 69, 529–541 (1981).CrossRefGoogle Scholar
  11. 11.
    A. Papoulis, A new algorithm in spectral analysis and band-limited extrapolation, IEEE Trans. Circuits Syst. CAS-22, 735–742 (1975).MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1989

Authors and Affiliations

  • Robert King
    • 1
  • Majid Ahmadi
    • 2
  • Raouf Gorgui-Naguib
    • 3
  • Alan Kwabwe
    • 4
  • Mahmood Azimi-Sadjadi
    • 5
  1. 1.Imperial CollegeLondonEngland
  2. 2.University of WindsorWindsorCanada
  3. 3.University of Newcastle upon TyneNewcastle upon TyneEngland
  4. 4.Imperial College and Bankers Trust CompanyLondonEngland
  5. 5.Colorado State UniversityFort CollinsUSA

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