Digital Watermarking Particle Swarm Optimization Based on Multi-wavelet

Watermark perceptibility and robustness must be ensured in order to enhance the practicality of digital watermarking. Taking human visual system characteristics into account fully, a particle swarm optimization method based on multi-wavelet digital watermarking is proposed. It utilizes Sa4 multiwavelet to embed digital watermark, chooses intermediate frequency in embedding digital watermark adaptively according to the size of every energy mass, and uses multi-objective optimization method based on particle swarm optimization to optimize and adjust the embedded depth to obtain optimal effect. Experiments show the new proposed algorithm not only ensures the quality of watermarkingembed image and robustness against attacks, but also accelerate the operating speed relative to genetic algorithms.

[1]  Yang Yi-xian The research developments and applications of digital watermarking , 2001 .

[2]  Zou Hai-lin Study on Methods of GPR Image De-noising Based on Multi-wavelets Transform , 2005 .

[3]  Yinghui Pan,et al.  Digital watermarking multi-objective optimization based on multi-wavelet , 2009, 2009 IEEE International Conference on Control and Automation.

[4]  P. Kumsawat,et al.  A new approach for optimization in image watermarking by using genetic algorithms , 2005, IEEE Transactions on Signal Processing.

[5]  Liang Tan,et al.  An Adaptive Middle Frequency Embedded Digital Watermark Algorithm Based on the DCT Domain , 2008, 2008 International Conference on Management of e-Commerce and e-Government.

[6]  Hai-hui Wang,et al.  A New Multiwavelet-Based Approach to Image Fusion , 2004, Journal of Mathematical Imaging and Vision.

[7]  Yang Dam Eo,et al.  Building 3D Geospatial Information Using Airborne Multi-Looking Digital Camera System , 2010, J. Convergence Inf. Technol..

[8]  Shinfeng D. Lin,et al.  A robust DCT-based watermarking for copyright protection , 2000, 2000 Digest of Technical Papers. International Conference on Consumer Electronics. Nineteenth in the Series (Cat. No.00CH37102).