• DocumentCode
    3548720
  • Title

    Vector quantization of images using fractal dimensions

  • Author

    Moyamoto, Takayuki ; Suzuki, Yukinori ; Saga, Sato ; Maeda, Junji

  • Author_Institution
    Dept. of Comput. Sci. & Syst. Eng., Muroran Inst. of Technol., Japan
  • fYear
    2005
  • fDate
    28-30 June 2005
  • Firstpage
    214
  • Lastpage
    217
  • Abstract
    In conventional vector quantization (VQ), for example, generalized Lloyd algorithm (GLA), an image is divided into blocks that are all the same size. This uniform division could be redundant. Furthermore, it could not attain both a high compression rate and high quality of encoded image. We propose a new method of VQ in which the block size to divide an image is determined by a local fractal dimension (LDF). Computational experiments were carried out to show the effectiveness of the method. Results of experiments showed that a compression rate of the proposed method is higher than that by the GLA under the condition that PSNR (Peak Signal-to-Noise Ratio) is more than 35.0 dB. Therefore, the proposed method is useful for practical image compression.
  • Keywords
    generalisation (artificial intelligence); image coding; image denoising; vector quantisation; encoded image; fractal dimension; generalized Lloyd algorithm; image compression; peak signal-to-noise ratio; vector quantization; Asynchronous transfer mode; B-ISDN; Clustering algorithms; Computer science; Decoding; Fractals; Image coding; PSNR; Pixel; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing in Industrial Applications, 2005. SMCia/05. Proceedings of the 2005 IEEE Mid-Summer Workshop on
  • Print_ISBN
    0-7803-8942-5
  • Type

    conf

  • DOI
    10.1109/SMCIA.2005.1466975
  • Filename
    1466975