A Coutourlet-Based Image Watermarking Using Generalized Gaussian Distribution Model

DOI

10.2991/icmt-13.2013.220How to use a DOI?

Keywords

Digital Watermarking; Generalized Gaussian distribution; Contourlet transform.

Abstract

With the increasing demands of copyright protection, digital watermarking has being paid more and more attention. In the design of a watermarking method, the modelling of signal by a general parametric family of statistical distributions plays an important role in many signal processing applications. Some conventional methods based on Gaussian distribution to model the image coefficients in the transform domain. In this paper, I proposed to adopt the generalized Gaussian distribution (GGD) for modelling the contourlet transform sub-band coefficients and for image watermarking scheme. The contourlet transform (perfect reconstruction and directional selectivity) is considered. Its improved robustness and imperceptibility are due to embedding in the directional subband with the highest energy. In watermark detection, the Neyman-Pearson (NP) detector is used to detect the watermark. Experimental results show that the effectiveness of the presented watermarking method and its robustness against common image processing and some kinds of geometric attacks.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhu Yin-fang
PY  - 2013/11
DA  - 2013/11
TI  - A Coutourlet-Based Image Watermarking Using Generalized Gaussian Distribution Model
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 1817
EP  - 1824
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.220
DO  - 10.2991/icmt-13.2013.220
ID  - Yin-fang2013/11
ER  -