基于遗传算法和SVD-DWT的图像水印优化嵌入方案
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摘要
鲁棒性与不可见性是数字水印的主要衡量标准,这两者相互制约,传统的数字水印算法很难将二者平衡,提出一种强鲁棒性的图像水印优化嵌入方案,基本思想是先将水印图像经过奇异值分解得到水印序列,然后在图像小波域内进行水印的嵌入和提取.采用遗传算法优化水印的嵌入位置,综合优化水印的鲁棒性和不可见性.水印嵌入是自适应的过程,且实现了盲提取.实验表明,该方案在水印遭受各种攻击时,能更好的恢复出清晰地水印图像,具有更强的鲁棒性和不可见性等优点.
The robustness and the invisibility are important properties in an efficient image watermarking system. Since they conflict with each other, a watermarking system is difficult to satisfy them at the same time.One good scheme to resolve this dilemma is to apply genetic algorithm(GA) to obtain the optimized solution.An optimal image watermarking technique based on GA was proposed. A SVD transform was utilized to obtain the watermark sequence, and then the watermark embedding and extraction were implemented in digital wavelet transform(DWT) domain. It actualizes self-adaptive embedding and blind extraction. The robustness and the invisibility of the watermarking system were optimized comprehensively by GA searching optimal parameters of embedding. Simulated results show that it can recover the watermarking image when the watermarking is aggressed. Compared with the technical background, it is of better robustness and invisibility.
The robustness and the invisibility are important properties in an efficient image watermarking system. Since they conflict with each other, a watermarking system is difficult to satisfy them at the same time.One good scheme to resolve this dilemma is to apply genetic algorithm(GA) to obtain the optimized solution.An optimal image watermarking technique based on GA was proposed. A SVD transform was utilized to obtain the watermark sequence, and then the watermark embedding and extraction were implemented in digital wavelet transform(DWT) domain. It actualizes self-adaptive embedding and blind extraction. The robustness and the invisibility of the watermarking system were optimized comprehensively by GA searching optimal parameters of embedding. Simulated results show that it can recover the watermarking image when the watermarking is aggressed. Compared with the technical background, it is of better robustness and invisibility.
引文
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[11]Akay B.A Study On Particle Swarm Optimization And Artificial Bee Colony Algorithms For Multilevel Thresholding[J].Applied Soft Computing,2013,13(6):3066-3091.
[2]Ali M,Chang W A,Siarry P.Differential evolution algorithm for the selection of optimal scaling factors in image watermarking[J].Engineering Applications of Artificial Intelligence,2014,31(4):15-26.
[3]Chen C H,Tang Y L,Wang C P,et al.A robust watermarking algorithm based on salient image features[J].Optik-International Journal for Light and Electron Optics,2014,125(3):1134-1140.
[4]朱光,张军亮.基于SVD和小波包分解的自适应鲁棒水印算法[J].计算机应用研究,2013,30(4):1230-1233.
[5]Elshazly E H,Faragallah O S,Abbas A M,et al.Robust and s ecure fractional wavelet image watermarking[J].Signal,Image and Video Processing,2015,9(1):89-98.
[6]Lang J,Zhang Z.Blind digital watermarking method in the fractional Fourier transform domain[J].Optics and Lasers in Engineering,2014,53(2):112-121.
[7]Chih-Chih Lai.An improved SVD-based watermark-ing scheme using human visual characteristics[J].Optics Communications,2011,32(4):7-19.
[8]Li L,Xu H H,Chang C C,et al.A novel image watermarking in redistributed invariant wavelet domain[J].Journal of Systems and Software,2011,84(6):923-929.
[9]Lai C C.An improved SVD-based watermarking scheme using human visual characteristics[J].Optics Communications,2011,284(4):938-944.
[10]Fan M Q,Wang H X,Li S K.Restudy on SVD-based watermarking scheme[J].Applied Mathematics and Computation,2008,203(2):926-930.
[11]Akay B.A Study On Particle Swarm Optimization And Artificial Bee Colony Algorithms For Multilevel Thresholding[J].Applied Soft Computing,2013,13(6):3066-3091.