Adaptive Window Singular Value Decomposition Method Based on Particle Swarm Optimization for Partial Discharge Denoising

Author(s):  
Bowen Zhang ◽  
Haibao Mu ◽  
Yiming Zheng ◽  
Jiangyang Zhan ◽  
Shao Xianjun ◽  
...  
2014 ◽  
Vol 22 (1) ◽  
Author(s):  
K. Loukhaoukha ◽  
M. Nabti ◽  
K. Zebbiche

AbstractThe major objective in developing a robust digital watermarking algorithm is to obtain the highest possible robustness without losing the visual imperceptibility. To achieve this objective, we proposed in this paper an optimal image watermarking scheme using multi-objective particle swarm optimization (MOPSO) and singular value decomposition (SVD) in wavelet domain. Having decomposed the original image into ten sub-bands, singular value decomposition is applied to a chosen detail sub-band. Then, the singular values of the chosen sub-band are modified by multiple scaling factors (MSF) to embed the singular values of watermark image. Various combinations of multiple scaling factors are possible, and it is difficult to obtain optimal solutions. Thus, in order to achieve the highest possible robustness and imperceptibility, multi-objective optimization of the multiple scaling factors is necessary. This work employs particle swarm optimization to obtain optimum multiple scaling factors. Experimental results of the proposed approach show both the significant improvement in term of imperceptibility and robustness under various attacks.


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