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

  • Authors:

  • Mohammad Ali Akhaee;S. Mohammad Ebrahim Sahraeian;Farokh Marvasti

  • Affiliations:

  • Advanced Communication Research Institute, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran;Genomic Signal Processing Lab, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX and Department of Electrical Engineering, Sharif University of Techn ...;Advanced Communication Research Institute, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 2010

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Abstract

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.