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Su Wengui, Shen Yulong, Wang Xiang. Two-Layer Reversible Watermarking Algorithm Using Difference Expansion[J]. Journal of Computer Research and Development, 2019, 56(7): 1498-1505. DOI: 10.7544/issn1000-1239.2019.20180736
Citation: Su Wengui, Shen Yulong, Wang Xiang. Two-Layer Reversible Watermarking Algorithm Using Difference Expansion[J]. Journal of Computer Research and Development, 2019, 56(7): 1498-1505. DOI: 10.7544/issn1000-1239.2019.20180736

Two-Layer Reversible Watermarking Algorithm Using Difference Expansion

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  • Published Date: June 30, 2019
  • Traditional difference expansion algorithm expands the difference between two adjacent pixels and embeds one bit of secret data to the expanded difference of the pixels of each pair if no overflow or underflow occurs. It can achieve an embedding rate up to 0.5bpp. The shortcoming of this algorithm is that it cannot provide higher embedding rate while keeping distortion low. To achieve higher capability, multiple-layer embedding is required for traditional difference expansion reversible watermarking. However, repetitive embedding of images in the same way does not effectively exploit the characteristics of difference expansion and the correlation among pixels, which will result in large image distortion. To achieve better capacity and superior performance, a novel difference expansion-based algorithm which enables two-layer embedding and pixel pair selection is proposed. The cover image is firstly divided into pairs of pixels. By analyzing the modification mechanism of pixel pairs in difference expansion, a different paring manner for each embedding is developed to better exploit the correlation among different pixel pairs. Furthermore, the mean of pixel pair is utilized as a predictor to select smooth pixel pairs for embedding, so that a higher peak signal-to-noise ratio can be achieved even when the embedding rate exceeds 0.5bpp. Experimental results verify that the proposed algorithm provides higher embedding capacity while maintaining lower distortion in image quality.
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