Watermark Extraction by Magnifying Noise and Applying Global Minimum Decoder

  • Authors:
  • Zhigeng Pan;Li Li;Mingmin Zhang;David Zhang

  • Affiliations:
  • Zhejiang University and Hangzhou Dianzi University;Hangzhou Dianzi University;Zhejiang University;Hong Kong Polytechnic University

  • Venue:
  • ICIG '04 Proceedings of the Third International Conference on Image and Graphics
  • Year:
  • 2004

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Abstract

For the classical watermark embedment model I=I + 驴W, the corresponding watermark detection has its limitation in its need of a fixed parameter for extracting watermarks. If the extraction parameter is too large, we cannot extract the watermark from the image that contains watermarks; if it is too small, the extracted watermarks may be blurred. This paper proposes a novel watermark extraction method. First, we treat the watermark information as noise for the watermarked image in its spatial domain. We then magnify the noise before detection. Next, we recover the watermark information by adjusting the extracted data from the frequency domain according to our global minimum method. Experimental results show that our watermark extraction method is more valid and accurate than the classical method. It can greatly reduce extraction errors.