Optimum decoder for an additive video watermarking with Laplacian noise in H.264

In this paper, we investigate an additive video watermarking method in H.264 standard in presence of the Laplacian noise. In some applications, due to the loss of some pixels or a region of a frame, we resort to Laplacian noise rather than Gaussian one. The embedding is performed in the transform domain; while an optimum and a sub-optimum decoder are derived for the proposed Laplacian model. Simulation results show that the proposed watermarking scheme has suitable performance with enough transparency required for watermarking applications.

• Publication year

  2015

• Venue

  ISC Conference on Information Security and Cryptology

• Publication date

  2015-06-04

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1109/ISCISC.2013.6767352arXiv 1506.01501
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A Cauchy distribution based video watermark detection for H.264/AVC in DCT domain

  2011cited by this paper
• Digital Watermarking and Steganography

  2009cited by this paper
• Generalized Embedding of Multiplicative Watermarks

  2009cited by this paper
• Contourlet based image watermarking using optimum detector in the noisy environment

  2008cited by this paper
• A Framework for Robust Watermarking of H.264-Encoded Video With Controllable Detection Performance

  2007cited by this paper
• Robust shift and add approach to superresolution

  2003cited by this paper
• The Laplace Distribution and Generalizations: A Revisit with Applications to Communications, Economics, Engineering, and Finance

  2001cited by this paper
• Detection in Laplace Noise

  1978cited by this paper
• Probability, Random Variables, and Stochastic Processes

  1966cited by this paper

• Robust Video Watermarking against H.264 and H.265 Compression Attacks

  2017cites this paper
• Optimum Decoder for Multiplicative Spread Spectrum Image Watermarking with Laplacian Modeling

  2016cites this paper
• Tatouage robuste d’images imprimées

  2015cites this paper