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A Wavelet Toolbox for Large Scale Image Processing

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Parallel Computation (ACPC 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1557))

Abstract

The wavelet transform has proven to be a valuable tool for image processing applications, like image compression and noise reduction. In this paper we present a scheme to process very large images that do not fit in the memory of a single computer, based on the software library WAILI (Wavelets with Integer Lifting). Such images are divided into blocks that are processed quasi independently, allowing efficient parallel programming. The blocking is almost completely transparent to the user.

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References

  1. R. Calderbank, I. Daubechies, W. Sweldens, and B.-L. Yeo. Wavelet transforms that map integers to integers. Appl. Comput. Harmon. Anal., 5(3):332–369, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  2. A. Cohen, I. Daubechies, and J. Feauveau. Bi-orthogonal bases of compactly supported wavelets. Comm. Pure Appl. Math., 45:485–560, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  3. S. G. Mallat. Multifrequency channel decompositions of images and wavelet models. IEEE Trans. Acoust. Speech Signal Process., 37(12):2091–2110, 1989.

    Article  Google Scholar 

  4. A. Said and W. A. Pearlman. Image compression using the spatial-orientation tree. In Proc. IEEE Int. Symp. Circuits and Syst., Chicago, IL, pages 279–282, May 1993.

    Google Scholar 

  5. J. M. Shapiro. Embedded image coding using zerotrees of wavelet coefficients. 41(12):3445–3462, 1993. IEEE Trans. Signal Process.

    Article  MATH  Google Scholar 

  6. W. Sweldens. The lifting scheme: A new philosophy in biorthogonal wavelet constructions. In A. F. Laine and M. Unser, editors, Wavelet Applications in Signal and Image Processing III, pages 68–79. Proc. SPIE 2569, 1995.

    Google Scholar 

  7. W. Sweldens. The lifting scheme: A construction of second generation wavelets. SIAM J. Math. Anal., 29(2), 1997.

    Google Scholar 

  8. G. Uytterhoeven, F. Van Wulpen, M. Jansen, D. Roose, and A. Bultheel. WAILI: A software library for image processing using integer wavelet transforms. In K.M. Hanson, editor, Medical Imaging 1998: Image Processing, volume 3338 of SPIE Proceedings, pages 1490–1501. The International Society for Optical Engineering, February 1998.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, B-3001, Heverlee, Belgium

    Geert Uytterhoeven, Dirk Roose & Adhemar Bultheel

Authors
  1. Geert Uytterhoeven
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  2. Dirk Roose
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  3. Adhemar Bultheel
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Editor information

Editors and Affiliations

  1. Forschungsinstitut für Softwaretechnologie, Hellbrunnerstr. 34, A-5020, Salzburg, Austria

    Peter Zinterhof

  2. Slovac Academy of Sciences, Institute of Mathematics, Laboratory for Informatics, Dubravska 9, P.O.Box 56, 840 00, Bratislava, Slovakia

    Marian Vajteršic

  3. Universität Salzburg, RIST++, Hellbrunnerstr. 34, A-5020, Salzburg, Austria

    Andreas Uhl

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© 1999 Springer-Verlag Berlin Heidelberg

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Uytterhoeven, G., Roose, D., Bultheel, A. (1999). A Wavelet Toolbox for Large Scale Image Processing. In: Zinterhof, P., Vajteršic, M., Uhl, A. (eds) Parallel Computation. ACPC 1999. Lecture Notes in Computer Science, vol 1557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49164-3_32

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  • DOI: https://doi.org/10.1007/3-540-49164-3_32

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65641-8

  • Online ISBN: 978-3-540-49164-4

  • eBook Packages: Springer Book Archive

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