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An Adaptive Fast Transform Based Image Compression

  • Kamil Stokfiszewski
  • Piotr S. Szczepaniak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5097)

Abstract

The paper deals with image compression performed using an adaptive fast transform-based method. The point of departure is a base scheme for fast computation of certain discrete transforms. The scheme can be interpreted in terms of the neural architecture whose parameters (neurons’ weights) can be adjusted during learning on set data, here images. The same basic network topology enables realization of diverse transformations. The results obtained for the task of image compression are presented and evaluated.

Keywords

Discrete Cosine Transform Discrete Fourier Transform Training Image Image Compression Inverse Transformation 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Kamil Stokfiszewski
    • 1
  • Piotr S. Szczepaniak
    • 1
    • 2
  1. 1.Institute of Computer ScienceTechnical University of LodzLodzPoland
  2. 2.Systems Research InstitutePolish Academy of SciencesWarsawPoland

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