Improved logarithmic spread transform dither modulation using a robust perceptual model

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• 作者：Wenbo Wan ; Ju Liu ; Jiande Sun ; Di Gao
• 关键词：Logarithmic STDM ; Perceptual JND model ; Watermarking robustness ; Edge strength
• 刊名：Multimedia Tools and Applications
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：75
• 期：21
• 页码：13481-13502
• 全文大小：1,168 KB
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Data Structures, Cryptology and Information Theory
  Special Purpose and Application-Based Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-7721
• 卷排序：75

文摘

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.