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A watermarking algorithm in encrypted image based on compressive sensing with high quality image reconstruction and watermark performance

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Abstract

In this paper, we propose a new digital watermarking algorithm in encrypted image based on compressive sensing measurements and 2-D discrete wavelet transform (DWT). Firstly, we process the original image through 2-D DWT to highlight the important part and unimportant part. For the important LL2 coefficient, before encrypting it by the traditional stream cipher, we divide it into blocks, and mark the blocks to get a sequence as the watermark position key. For other wavelet coefficients, we select two different compressive sensing measurement matrices to simultaneously encrypt and compress them, respectively. Then we embed a watermark into the high frequency coefficient measurements except HH1 section based on the watermark position key. Finally, the watermarked image is scrambled to enhance the security. In this algorithm, compressive sensing is adopted for compression and encryption, and watermark is embedded in the measurements values. It can not only increase the watermark embedding capacity and robustness, but also utilize the reconstruction characteristic of compressive sensing to get higher-quality recovered image. The experimental results verify the validity and the reliability of the proposed algorithm.

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Acknowledgments

The work described in this paper was funded by the National Natural Science Foundation of China (Grant Nos. 61272043, 61302161, 61472464, 61502399, 61572089), the Natural Science Foundation of Chongqing Science and Technology Commission (Grant Nos. cstc2012jjA40017, cstc2013jcyjA40017, cstc2013jjB40009, cstc2015jcyjA40039) and the Fundamental Research Funds for the Central Universities (Grant Nos. 106112013CDJZR180005, 106112014CDJZR185501).

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Xiao, D., Chang, Y., Xiang, T. et al. A watermarking algorithm in encrypted image based on compressive sensing with high quality image reconstruction and watermark performance. Multimed Tools Appl 76, 9265–9296 (2017). https://doi.org/10.1007/s11042-016-3532-x

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  • DOI: https://doi.org/10.1007/s11042-016-3532-x

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