Fractal Image Compression Based on Adaptive Tessellations (bibtex)
by Frank Davoine
Abstract:
The principle of fractal image coding presented in this paper is based on the theory of L-IFS (Local Iterated Function Systems). The algorithm exploits the fact that a real-world image is formed approximately of transformed copies of parts of itself. Thus, the construction of fractal codes is directly made on partitions of the image support. It is based on piece-wise similarities between blocks of different sizes.\\ The paper starts with a regular block based approach first proposed by Jacquin. To improve the algorithm, adaptive partitions are proposed with, in particular, the Delaunay triangulation. The results show an improvement in computing times, compression ratios and visual quality of reconstructed images.
Reference:
Fractal Image Compression Based on Adaptive Tessellations (Frank Davoine), Technical report, PRIP, TU Wien, 1993.
Bibtex Entry:
@TechReport{PTR-Davoine93a,
  author =	 "Frank Davoine",
  institution =	 "PRIP, TU Wien",
  number =	 "PRIP-TR-025",
  title =	 "Fractal {I}mage {C}ompression {B}ased on {A}daptive
                  {T}essellations",
  year =	 "1993",
  url =		 "ftp://ftp.prip.tuwien.ac.at/pub/publications/trs/tr25.ps.gz",
  abstract =	 "The principle of fractal image coding presented in
                  this paper is based on the theory of L-IFS (Local
                  Iterated Function Systems). The algorithm exploits
                  the fact that a real-world image is formed
                  approximately of transformed copies of parts of
                  itself. Thus, the construction of fractal codes is
                  directly made on partitions of the image support. It
                  is based on piece-wise similarities between blocks
                  of different sizes.\\ The paper starts with a
                  regular block based approach first proposed by
                  Jacquin. To improve the algorithm, adaptive
                  partitions are proposed with, in particular, the
                  Delaunay triangulation. The results show an
                  improvement in computing times, compression ratios
                  and visual quality of reconstructed images.",
}
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