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An Adaptive Embedding Strength Watermarking Algorithm Based on Shearlets’ Capture Directional Features

Author

Listed:
  • Qiumei Zheng

    (College of Computer Science and Technology, China University of Petroleum, Qingdao 266580, China)

  • Nan Liu

    (College of Computer Science and Technology, China University of Petroleum, Qingdao 266580, China)

  • Fenghua Wang

    (College of Computer Science and Technology, China University of Petroleum, Qingdao 266580, China)

Abstract

The discrete wavelet transform (DWT) is unable to represent the directional features of an image. Similarly, a fixed embedding strength is not able to establish an ideal balance between imperceptibility and robustness of a watermarked image. In this work, we propose an adaptive embedding strength watermarking algorithm based on shearlets’ capture directional features (S-AES). We improve the watermarking algorithm in the domain of DWT using non-subsampled shearlet transform (NSST). The improvement is made in terms of coping with anti-geometric attacks. The embedding strength is optimized by artificial bee colony (ABC) to achieve higher robustness under the premise of satisfying imperceptibility. The principle components (PC) of the watermark are embedded into the host image to overcome the false positive problem. The simulation results show that the proposed algorithm has better imperceptibility and strong robustness against multi-attacks, especially those of high intensity.

Suggested Citation

  • Qiumei Zheng & Nan Liu & Fenghua Wang, 2020. "An Adaptive Embedding Strength Watermarking Algorithm Based on Shearlets’ Capture Directional Features," Mathematics, MDPI, vol. 8(8), pages 1-19, August.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:8:p:1377-:d:400071
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    References listed on IDEAS

    as
    1. Xiaoyi Zhou & Chunjie Cao & Jixin Ma & Longjuan Wang, 2018. "Adaptive Digital Watermarking Scheme Based on Support Vector Machines and Optimized Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, March.
    2. Jian Zhao & Wensheng Xu & Shunli Zhang & Shuaishuai Fan & Wanru Zhang, 2016. "A Strong Robust Zero-Watermarking Scheme Based on Shearlets’ High Ability for Capturing Directional Features," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-11, October.
    3. Musrrat Ali & Chang Wook Ahn & Millie Pant & Patrick Siarry, 2016. "A Reliable Image Watermarking Scheme Based on Redistributed Image Normalization and SVD," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-15, February.
    4. Yewen Li & Wei Song & Xiaobing Zhao & Juan Wang & Lizhi Zhao, 2019. "A Novel Image Tamper Detection and Self-Recovery Algorithm Based on Watermarking and Chaotic System," Mathematics, MDPI, vol. 7(10), pages 1-17, October.
    5. Xinchun Cui & Yuying Niu & Xiangwei Zheng & Yingshuai Han, 2018. "An optimized digital watermarking algorithm in wavelet domain based on differential evolution for color image," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-15, May.
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    Cited by:

    1. Yimeng Zhao & Chengyou Wang & Xiao Zhou & Zhiliang Qin, 2022. "DARI-Mark: Deep Learning and Attention Network for Robust Image Watermarking," Mathematics, MDPI, vol. 11(1), pages 1-16, December.

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