数字水印算法中的粒子群算法和遗传算法参数估计

Varsha Parashar, Garima Mehta
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引用次数: 2

摘要

数字水印方案为各方之间的多媒体交换提供了版权保护和认证,特别是对数字媒体。提出了一种利用粒子天鹅优化和遗传算法搜索优化元启发式技术对数字媒体进行增强的安全水印算法。图像质量是使用均方误差、归一化互相关和峰值信噪比来计算图像中相对于亮度、对比度和相关损失等参数的失真或噪声。利用粒子天鹅优化和遗传算法选择系数,将离散小波变换后的高阶系数嵌入到主图像上。对不同的攻击进行建模,以获得不可感知性和鲁棒性。实验结果证明了所提方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PSO and GA parameters estimation for digital watermarking algorithm
The digital watermarking schemes provide multimedia exchanged between parties with copyright protection and authentication especially to digital media. In this paper a secured watermarking algorithm for strengthening of digital media using Particle Swan Optimization and Genetic Algorithm search optimization meta-heuristic techniques is proposed. Image quality is computed using Mean Squared Error, Normalized Cross Correlation and Peak Signal-to-Noise Ratio to calculate the distortion or noise in the image with respect to parameters like luminance, contrast and correlation loss. The coefficient is selected using Particle Swan Optimization and Genetic Algorithm to embed Discrete Wavelet Transformed high level coefficients on the host image. Different attacks are modelled to access the imperceptibility and robustness. The experimental results are reported to demonstrate the effective solution of the proposed schemes.
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