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Contourlet-based image watermarking using optimum detector in a noisy environment

Akhaee, M. A ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/TIP.2009.2038774
  3. Abstract:
  4. In this paper, an improved multiplicative image watermarking system is presented. Since human visual system is less sensitive to the image edges, watermarking is applied in the contourlet domain, which represents image edges sparsely. In the presented scheme, watermark data is embedded in directional subband with the highest energy. By modeling the contourlet coefficients with General Gaussian Distribution (GGD), the distribution of watermarked noisy coefficients is analytically calculated. The tradeoff between the transparency and robustness of the watermark data is solved in a novel fashion. At the receiver, based on the Maximum Likelihood (ML) decision rule, an optimal detector by the aid of channel side information is proposed. In the next step, a blind extension of the suggested algorithm is presented using the patchwork idea. Experimental results confirm the superiority of the proposed method against common attacks, such as Additive White Gaussian Noise (AWGN), JPEG compression, and rotation attacks, in comparison with the recently proposed techniques
  5. Keywords:
  6. Contourlet transform ; Maximum likelihood detector ; Multiplicative image watermarking ; Additive white Gaussian noise ; Channel side information ; Contourlet coefficients ; Contourlet transform ; Contourlets ; Decision rules ; General Gaussian distribution ; Human visual system ; Image edge ; Image watermarking ; Image watermarking systems ; JPEG compression ; Maximum likelihood detectors ; Noisy environment ; Optimal detectors ; Optimum detectors ; Sub-bands ; Additive noise ; Algorithms ; Detectors ; Gaussian noise (electronic) ; Maximum likelihood ; Signal detection ; Turbo codes ; Watermarking ; White noise ; Edge detection
  7. Source: IEEE Transactions on Image Processing ; Volume 19, Issue 4 , 2010 , Pages 967-980 ; 10577149 (ISSN)
  8. URL: http://ieeexplore.ieee.org/abstract/document/5356158