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Dual image watermarking by exploiting the properties of selected DCT coefficients with JND modeling

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Abstract

The distinctive properties of partly sign-altered (PSA) coefficients in discrete cosine transform (DCT) domain are explored to achieve effective dual blind image watermarking. A host image is divided into non-overlapped blocks, each of which is then converted to a DCT representation separately. For each block, low-frequency DCT coefficients are selected for dual binary watermarking. The first binary bit is applied to the mean value of the PSA coefficients. Our formulation takes into account of human psychovisual characteristics. A stair-like quantization function is designed to not only regulate embedding strength but accommodate extra embedding for blocks with high contrast masking. In case second watermarking is requested, we tactically adjust the standard deviation of the PSA coefficients while keeping the PSA mean intact. The embedding strengths with respect to the involved parameters in the first and second watermarking are analytically examined. Experiment results indicate that the proposed scheme is capable of achieving excellent robustness at a peak signal-to-noise ratio (PSNR) around 38.7 dB. In particular, the exploitation of just noticeable distortion helps to enhance the robustness of the first watermark without causing noticeable quality degradation. The secondary watermark is embedded at the cost of approximately 1 dB PSNR. Yet the resultant performance is comparable with other compared methods in terms of bit error rates.

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Acknowledgements

This work was supported by the Ministry of Science and Technology, Taiwan, ROC, under Grants MOST 104-2221-E-197-023 & MOST 105-2221-E-197-019.

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  1. Department of Electronic Engineering, National I-Lan University, Yi-Lan, Taiwan, 26041, Republic of China

    Hwai-Tsu Hu & Jieh-Ren Chang

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  1. Hwai-Tsu Hu
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Correspondence to Hwai-Tsu Hu.

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Hu, HT., Chang, JR. Dual image watermarking by exploiting the properties of selected DCT coefficients with JND modeling. Multimed Tools Appl 77, 26965–26990 (2018). https://doi.org/10.1007/s11042-018-5900-1

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