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Improved Reversible Visible Watermarking Based on Adaptive Block Partition

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Digital Forensics and Watermarking (IWDW 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10431))

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Abstract

Visible watermarking is a useful technique to perceptually protect the copyright while the reversible technique can help losslessly recover the original image. A reversible visible image watermarking scheme based on difference-expansion and adaptive block partition is presented in this paper. First, the cover image is divided into non-overlapped \(k \times k\) sized blocks. Then, an adaptive visual effect factor for each block is calculated by non-watermarked blocks and estimated watermarked blocks in its neighborhood to embed the visible watermark. Since the information in watermarking region is not used, authorized users can exactly recover the original cover image without the availability of the watermark in the recovery process. Afterwards, one watermark bit is embedded into each block based on the conventional difference-expansion method. To reduce the exceeding number which denotes the pixel whose values is larger than 255 or less than 0 generated in watermark bit embedding procedure, an adaptive block partition strategy is utilized in the proposed method. Experimental results show that compared with the related work, the proposed method can greatly reduce the exceeding numbers and the visual effect is better at the same time.

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Acknowledgement

This work is supported by National Natural Science Foundation of China under contract Nos. U1636206 and 61572052.

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Correspondence to Zongming Guo .

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Yang, G., Qi, W., Li, X., Guo, Z. (2017). Improved Reversible Visible Watermarking Based on Adaptive Block Partition. In: Kraetzer, C., Shi, YQ., Dittmann, J., Kim, H. (eds) Digital Forensics and Watermarking. IWDW 2017. Lecture Notes in Computer Science(), vol 10431. Springer, Cham. https://doi.org/10.1007/978-3-319-64185-0_23

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  • DOI: https://doi.org/10.1007/978-3-319-64185-0_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64184-3

  • Online ISBN: 978-3-319-64185-0

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