Semisubsampled Wavelet Transform Based Image Watermarking with Strong Robustness to Rotation Attacks

نویسندگان

  • Yingkun Hou
  • Chunxia Zhao
  • Mingxia Liu
  • Zhengli Zhu
  • Deyun Yang
چکیده

In this paper, we develop a novel transform called semisubsampled wavelet transform (SSWT) and employ it to image watermarking. SSWT consists of two parts, one is nonsubsampled tight frame transform, the other is critically sampled wavelet transform (WT). Embedding watermark into the low-frequency sub-band of SSWT, the imperceptibility and robustness of watermark can be significantly improved comparing with some existing watermarking schemes. Experimental results show that proposed blind watermarking scheme is robust against JPEG compression, Gaussian noise, Wiener filtering and median filtering attacks. For rotation attack, we propose a novel watermarking resynchronization approach, the ideal watermark can be always successfully extracted after resynchronization operation to any angle rotated watermarked image. Experimental results show that the proposed resynchronization approach is considerably effective and feasible.

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عنوان ژورنال:
  • Journal of Multimedia

دوره 5  شماره 

صفحات  -

تاریخ انتشار 2010