• DocumentCode
    2663478
  • Title

    Improving fractal image compression schemes through quantization and entropy coding

  • Author

    Ghazel, M. ; Khandani, A.K. ; Vrscay, E.R.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
  • Volume
    2
  • fYear
    1998
  • fDate
    24-28 May 1998
  • Firstpage
    661
  • Abstract
    We explore the transform coefficients of various fractal-based schemes for statistical dependence and exploit correlations to improve the compression capabilities of these schemes. In most of the standard fractal-based schemes, the transform coefficients exhibit a degree of linear dependence that can be exploited by using an appropriate vector quantizer such as the LBG algorithm. Additional compression is achieved by lossless Huffman coding of the quantized coefficients
  • Keywords
    Huffman codes; entropy codes; fractals; image coding; statistical analysis; transforms; vector quantisation; LBG algorithm; correlations; entropy coding; fractal image compression schemes; linear dependence; lossless Huffman coding; quantization; quantized coefficients; statistical dependence; transform coefficients; vector quantizer; Entropy coding; Fractals; Huffman coding; Image coding; Image resolution; Image storage; Inverse problems; Mathematics; Transform coding; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
  • Conference_Location
    Waterloo, Ont.
  • ISSN
    0840-7789
  • Print_ISBN
    0-7803-4314-X
  • Type

    conf

  • DOI
    10.1109/CCECE.1998.685583
  • Filename
    685583