Vector Quantization-Fractal Image Coding Algorithm Based on Delaunay Triangulation

  • Zahia Brahimi
  • KarimaAit Saadi
  • Noria Baraka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1685)


In this paper, we present a flexible partitioning scheme for fractal image compression based on adaptive Delaunay triangulation. Such partition is computed on an initial set of points obtained with a split and merge algorithm in a grey level dependent way. The triangulation is fully flexible and returns a limited number of blocks allowing good compression Ratios Moreover, a vector quantization algorithm is implemented on pixel histograms directly generated from the triangulation. The aim is to reduce the number of comparisons between the two sets of blocks involved in fractal image compression by keeping only the best representative triangles in the domain blocks set. Quality coding results are achieved at rates between 0.06 b/pixel and 0.2 b/pixel for a PSNR between 22 and 25 dB depending on the nature of the original image and on the number of triangles refereed.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Zahia Brahimi
    • 1
  • KarimaAit Saadi
    • 1
  • Noria Baraka
    • 1
  1. 1.128, Chemin Mohamed GacemAlgerAlgeria

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