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Transform Vector Quantization of Images in One Dimension

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Rough Sets and Current Trends in Computing (RSCTC 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1424))

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Abstract

In this paper there is enclosed a description of the hybrid system for black and white (256 by 256 pixels) images compression. The system includes the following procedures: image decomposition (8×8, 16×16 blocks), DCT transformation, “zig-zag” scanning, product code vector quantization (one- dimensional block) and a bit allocation. The standard LBG algorithm for codebook design has been enriched with the simulated annealing procedure for avoiding the local minima. Standard vector quantization in two-dimensional transform space has been investigated for comparison.

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References

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Author information

Authors and Affiliations

  1. Warsaw University of Technology, Pl. Politechniki 1, PL00-660, Warsaw, Poland

    Remigiusz J. Rak

Authors
  1. Remigiusz J. Rak
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Editor information

Editors and Affiliations

  1. Institute of Mathematics, Warsaw University of Technology, Pl. Politechniki 1, 00-665, Warszawa, Poland

    Lech Polkowski

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warszawa, Poland

    Andrzej Skowron

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© 1998 Springer-Verlag Berlin Heidelberg

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Rak, R.J. (1998). Transform Vector Quantization of Images in One Dimension. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_49

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  • DOI: https://doi.org/10.1007/3-540-69115-4_49

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64655-6

  • Online ISBN: 978-3-540-69115-0

  • eBook Packages: Springer Book Archive

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