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Image magnification based on similarity analogy

Author

Listed:
  • Chen, Zuoping
  • Ye, Zhenglin
  • Wang, Shuxun
  • Peng, Guohua

Abstract

Aiming at the high time complexity of the decoding phase in the traditional image enlargement methods based on fractal coding, a novel image magnification algorithm is proposed in this paper, which has the advantage of iteration-free decoding, by using the similarity analogy between an image and its zoom-out and zoom-in. A new pixel selection technique is also presented to further improve the performance of the proposed method. Furthermore, by combining some existing fractal zooming techniques, an efficient image magnification algorithm is obtained, which can provides the image quality as good as the state of the art while greatly decrease the time complexity of the decoding phase.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:5:p:2370-2375
    DOI: 10.1016/j.chaos.2007.10.031
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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.
    2. Wu, Ming-Sheng & Teng, Wei-Chih & Jeng, Jyh-Horng & Hsieh, Jer-Guang, 2006. "Spatial correlation genetic algorithm for fractal image compression," Chaos, Solitons & Fractals, Elsevier, vol. 28(2), pages 497-510.
    3. 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.
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