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Robust and blind image watermarking via circular embedding and bidimensional empirical mode decomposition

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A Correction to this article was published on 29 July 2020

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Abstract

In this paper, a robust and blind image watermarking algorithm via circular embedding and bidimensional empirical mode decomposition (BEMD) is developed. First, the watermark image is scrambled by Arnold transform to increase the security of the algorithm. Second, the Hilbert curve is adopted to reduce the scrambled 2D watermark image to one-dimensional watermark signal. Third, the host image is decomposed by BEMD to obtain the multi-scale representation in the forms of intrinsic mode functions (IMFs) and a residue. Then, the extreme points of the IMFs are extracted as the embedding locations. Finally, the one-dimensional watermark signal is repeatedly and cyclically embedded in the extreme locations of the first IMF according to the texture masking characteristics of the human visual system, which greatly improves the ability of our algorithm against various attacks. The final watermarked image is reconstructed by combining the modified first IMF and the residual. The watermark can be successfully extracted without resorting to the original host image. Furthermore, image correction can be applied before image watermarking extraction if there are geometric attacks in watermarked image. A large number of experimental results and thorough evaluations confirm that our method can obtain higher imperceptibility and robustness under different types of attacks, and achieve better performance than the current state-of-the-art watermarking algorithms, especially in large-scale cropping attack, JPEG compression, Gaussian noise, sharpening, Gamma correction, scaling, histogram equalization, and rotation attacks.

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  • 29 July 2020

    The publication of this article unfortunately contained mistakes. The affiliation and the biography of Ling Du were not correct. The corrected affiliation and bibliography is given below.

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Funding

This research is supported in part by National Science Foundation of USA (IIS-1715985 and IIS-1812606), National Natural Science Foundation of China (No. 61672149, 61602341, 61672077, 61532002, 61602344, 61802279, 61872347); Natural Science Foundation of Tianjin (18JCQNJC00100). The Science & Technology Development Fund of Tianjin Education Commission for Higher Education (Grant No. 2018KJ222).

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Authors and Affiliations

  1. School of Mathematical Sciences, Tiangong University, Tianjin, 300387, China

    Xiaochao Wang & Ling Du

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Kun Hu

  3. School of Sciences, Northeast Electric Power University, Jilin, 132012, China

    Jianping Hu

  4. Department of Computer Science, University of Surrey, Guildford, Surrey, GU2 7XH, UK

    Anthony T. S. Ho

  5. Department of Computer Science, Stony Brook University, Stony Brook, NY, 11794-4400, USA

    Hong Qin

Authors
  1. Xiaochao Wang
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  2. Kun Hu
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  3. Jianping Hu
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  4. Ling Du
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  5. Anthony T. S. Ho
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  6. Hong Qin
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Correspondence to Jianping Hu.

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Wang, X., Hu, K., Hu, J. et al. Robust and blind image watermarking via circular embedding and bidimensional empirical mode decomposition. Vis Comput 36, 2201–2214 (2020). https://doi.org/10.1007/s00371-020-01909-2

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