Dual image watermarking by exploiting the properties of selected DCT coefficients with JND modeling
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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.
KeywordsDual image watermarking Discrete cosine transform Partly sign-altered mean Just noticeable distortion Contrast masking
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.
- 1.Ahumada JAJ, Peterson HA (1992) Luminance-model-based DCT quantization for color image compression. In: Proc. SPIE, p 365–374Google Scholar
- 2.Arnold VI, Avez A (1968) Ergodic problems of classical mechanics. The mathematical physics monograph series. Benjamin, New YorkGoogle Scholar
- 11.Cox IJ (2008) Digital watermarking and steganography. The Morgan Kaufmann series in multimedia information and systems, 2nd edn. Morgan Kaufmann Publishers, AmsterdamGoogle Scholar
- 24.Leng L, Zhang J, Khan MK, Chen X, Alghathbar K (2010) Dynamic weighted discrimination power analysis: a novel approach for face and palmprint recognition in DCT domain. Int J Phys Sci 5(17):2543–2554Google Scholar
- 26.Liao X, Yin J, Guo S, Li X, Sangaiah AK (2017) Medical JPEG image steganography based on preserving inter-block dependencies. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2017.08.020
- 32.Santhi V, Rekha N, Tharini S (2008) A hybrid block based watermarking algorithm using DWT-DCT-SVD techniques for color images. In: Int. Conf. on Computing, Communication and Networking, 18–20 Dec 2008. p 1–7Google Scholar
- 38.USC-SIPI image database. Available from http://sipi.usc.edu/database/
- 43.Watson AB (1993) DCT quantization matrices visually optimized for individual images. In: Proc. SPIE. p 202–216Google Scholar
- 45.Zhang G, Wang S, Wen Q (2004) An adaptive block-based blind watermarking algorithm. In: 7th Int. Conf. on Signal Processing (ICSP). p 2294–2297Google Scholar
- 47.Zheng D, Liu Y, Zhao J (2006) A survey of RST invariant image watermarking algorithms. In: Canadian Conf. on Electrical and Computer Engineering, Ottawa, Canada. p 2086–2089Google Scholar