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Discrete wavelet transform-based simple range classification strategies for fractal image coding

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Abstract

An efficient fractal method based on discrete wavelet transfer is proposed in this paper. Before encoding, images with one-level wavelet transform are first partitioned into four subbands, which classify the range blocks as four types. An accelerated fractal coding method called variance sorting (VS) scheme with high reconstructed quality is addressed for the low-frequency components. Hereafter, the low-frequency part rebuilt performs one-level wavelet decomposition once again. The first-level high-frequency subbands excluding the diagonal directions are predicted according to the next coarser frequency scale in the same directions. Simulation experimental results compared with other classification algorithms demonstrate that the proposed method can obtain high compression ratio and reduce the encoding time without significant loss in the reconstructed image quality.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (Nos: 61370145, 61173183, and 60973152), the Doctoral Program Foundation of Institution of Higher Education of China (No: 20070141014), Program for Liaoning Excellent Talents in University (No: LR2012003), the National Natural Science Foundation of Liaoning province (No: 20082165) and the Fundamental Research Funds for the Central Universities (No: DUT12JB06).

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  1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, China

    Xing-Yuan Wang & Dou-Dou Zhang

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  1. Xing-Yuan Wang
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  2. Dou-Dou Zhang
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Correspondence to Xing-Yuan Wang.

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Wang, XY., Zhang, DD. Discrete wavelet transform-based simple range classification strategies for fractal image coding. Nonlinear Dyn 75, 439–448 (2014). https://doi.org/10.1007/s11071-013-1076-4

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  • DOI: https://doi.org/10.1007/s11071-013-1076-4

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