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Interpolation decoding method with variable parameters for fractal image compression

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  • He, Chuan-jiang
  • Li, Gao-ping
  • Shen, Xiao-na

Abstract

The interpolation fractal decoding method, which is introduced by [He C, Yang SX, Huang X. Progressive decoding method for fractal image compression. IEE Proc Vis Image Signal Process 2004;3:207–13], involves generating progressively the decoded image by means of an interpolation iterative procedure with a constant parameter. It is well-known that the majority of image details are added at the first steps of iterations in the conventional fractal decoding; hence the constant parameter for the interpolation decoding method must be set as a smaller value in order to achieve a better progressive decoding. However, it needs to take an extremely large number of iterations to converge. It is thus reasonable for some applications to slow down the iterative process at the first stages of decoding and then to accelerate it afterwards (e.g., at some iteration as we need). To achieve the goal, this paper proposed an interpolation decoding scheme with variable (iteration-dependent) parameters and proved the convergence of the decoding process mathematically. Experimental results demonstrate that the proposed scheme has really achieved the above-mentioned goal.

Suggested Citation

  • He, Chuan-jiang & Li, Gao-ping & Shen, Xiao-na, 2007. "Interpolation decoding method with variable parameters for fractal image compression," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1429-1439.
    • Handle: RePEc:eee:chsofr:v:32:y:2007:i:4:p:1429-1439
    DOI: 10.1016/j.chaos.2005.11.058
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    References listed on IDEAS

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    1. He, Chuanjiang & Xu, Xiaozeng & Yang, Jing, 2006. "Fast fractal image encoding using one-norm of normalised block," Chaos, Solitons & Fractals, Elsevier, vol. 27(5), pages 1178-1186.
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    Cited by:

    1. Lai, Fu-Jou & Huang, Yueh Min, 2009. "Probability- and curve-based fractal reconstruction on 2D DEM terrain profile," Chaos, Solitons & Fractals, Elsevier, vol. 41(2), pages 970-978.
    2. Chen, Zuoping & Ye, Zhenglin & Wang, Shuxun & Peng, Guohua, 2009. "Image magnification based on similarity analogy," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2370-2375.
    3. Lu, Jian & Ye, Zhongxing & Zou, Yuru & Ye, Ruisong, 2008. "An enhanced fractal image denoising algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 38(4), pages 1054-1064.

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