Fractal image compression with variance and mean

  • Authors:
  • Yung-Gi Wu;Ming-Zhi Huang;Yu-Ling Wen

  • Affiliations:
  • Inst. of Appl. Inf., Leader Univ., Tainan, Taiwan;Inst. of Appl. Inf., Leader Univ., Tainan, Taiwan;Inst. of Appl. Inf., Leader Univ., Tainan, Taiwan

  • Venue:
  • ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
  • Year:
  • 2003

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Abstract

Although fractal image compression has high quality at high compression ratio, it needs a lot of encoding time so that it has not been widely applied as other coding schemes in the field of image compression. In this paper, an algorithm is devised to improve this drawback. We utilize mean and variance to classify image blocks and combine the transformation reduction techniques to decrease the encoding time. The experimental result shows that our proposed method makes the encoder about 480 times faster than the conventional fractal compression method and the quality is imperceptible to that of the conventional fractal encoding algorithm while decreasing the bit rate as well.