Improved logarithmic spread transform dither modulation using a robust perceptual model
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In the quantization-based watermarking framework, the perceptual just noticeable distortion (JND) model has been widely used to determine the quantization step size, as it can be used for the better tradeoff between imperceptibility and robustness. However, the calculated JND values will change as watermark embedding can affect the texture and luminance of the image. Consequently, the changes of JND values will lead to watermark-extraction errors. In this paper, the authors present an improved logarithmic spread transform dither modulation (STDM) watermarking approach using a best-matched DCT-based perceptual JND model, which can be insensitive to the changes caused by watermark embedding and attacks. Experimental results confirm the improved robustness performance of the JND model in the watermarking framework. Simulation results show that the proposed scheme is more robust than the existing JND model-based watermarking algorithms with the uniform fidelity, and our proposed scheme has a superior performance compared with the former proposed perceptual STDM schemes.
KeywordsLogarithmic STDM Perceptual JND model Watermarking robustness Edge strength
This work was supported by the Special Development Fund of Shandong Information Industry (2011R0116), the Natural Science Foundation of Shandong Province (2014ZRE27336) and the National Natural Science Foundation of China (61001180).
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