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Spectrum-estimation based lossless information recovery for sparse array patterns

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Abstract

One of the open problems in lossless information hiding research is how to get adaptively better difference image architectures for given applications. In this paper we propose a simple and efficient approach to predict high-similar interpolation image from its sparse pattern and spectral expansion. After difference operator, peak value of the spike is very high. This method also provides a mathematic framework for evaluating de-correlating algorithm and can therefore be used to benchmark new algorithms. Finally, a proper reversible data hiding algorithm is also enclosed which refers conventional difference expansion principle. Overflow and underflow is considered in the fusion way. Simulations results demonstrate and verify that our new approach is much effective than local difference expansion method with good generalization performance.

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Authors and Affiliations

  1. School of Communication and Information Engineering, Shanghai University, Shanghai, 200072, P.R. China

    Guorui Feng, Zhenxing Qian & Xinpeng Zhang

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  1. Guorui Feng
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  2. Zhenxing Qian
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  3. Xinpeng Zhang
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Correspondence to Xinpeng Zhang.

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Feng, G., Qian, Z. & Zhang, X. Spectrum-estimation based lossless information recovery for sparse array patterns. Telecommun Syst 49, 163–169 (2012). https://doi.org/10.1007/s11235-010-9365-4

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  • DOI: https://doi.org/10.1007/s11235-010-9365-4

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