• DocumentCode
    2793140
  • Title

    Hybrid encoding analysis of fractal image compression method based on wavelet transform

  • Author

    Xu, Xiao-yan ; Chen, Philip ; Dai, Juan

  • Author_Institution
    Electr. Eng. Dept., Shanghai Maritime Univ., Shanghai
  • Volume
    5
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    2886
  • Lastpage
    2889
  • Abstract
    Firstly, the principle and characteristics of fractal image encoding is introduced, and a kind of hybrid image compression method is developed for the improvement of image compression quality, which is the combination of fractal image encoding and wavelet decomposition. In the process of encoding, the image is dealt by three level wavelet decomposition, and the high frequency section of the decomposed image adopts scatheless predicting encoding, while the low frequency section adopts fractal compression encoding. In the process of decoding, the high frequency section carries out scatheless predicting decoding, while the low frequency section is decoded to IFS (iterative function system) code which is used for subimage reconstruction. The experimental result shows that the application of the designed hybrid image compression method can increase the signal-to-noise ratio of an image while the high compression ratio of the image is guaranteed.
  • Keywords
    data compression; image coding; image reconstruction; wavelet transforms; IFS; fractal image compression method; hybrid encoding analysis; iterative function system; signal-to-noise ratio; subimage reconstruction; wavelet transform; Fractals; Frequency; Image analysis; Image coding; Image reconstruction; Iterative decoding; Signal design; Signal to noise ratio; Wavelet analysis; Wavelet transforms; Fractal Image Encoding; Hybrid Encoding; IFS (Iterative Function System); Wavelet Decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620900
  • Filename
    4620900