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Distribution independent blindwatermarking

Sahraeian, M. E ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. DOI: 10.1109/ICIP.2009.5414116
  3. Publisher: IEEE Computer Society , 2009
  4. Abstract:
  5. In this paper, a new blind scaling based watermarking approach is presented. The host signal is assumed to be stationary Gaussian with first-order autoregressive model. Partitioning the host signal into two separate parts, the data is embedded in one part and the other is kept unchanged for blind parameter estimation. Driving the distribution of the decision variable we have suggested a maximum likelihood decoding algorithm which is independent of the host signal distribution and can be applied for any transform domains. The proposed algorithm is applied to both artificial Gaussian autoregressive signals as well as various test images. Experimental results confirm the independence of the decoder performance to the host signal distribution and its great robustness against common attacks. ©2009 IEEE
  6. Keywords:
  7. Gaussian ratio distribution ; Scaling based embedding ; Algorithms ; Decoding ; Image processing ; Imaging systems ; Parameter estimation ; Signal processing ; Watermarking ; Auto regressive models ; Autoregressive signals ; Decision variables ; Decoder performance ; First-order ; Gaussians ; Host signals ; Maximum likelihood decoder ; Maximum likelihood decoders ; Maximum-likelihood decoding algorithms ; Test images ; Transform domain ; Maximum likelihood estimation
  8. Source: Proceedings - International Conference on Image Processing, ICIP, 7 November 2009 through 10 November 2009, Cairo ; 2009 , Pages 125-128 ; 15224880 (ISSN); 9781424456543 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/5414116