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A wavelet-based particle swarm optimization algorithm for digital image watermarking

机译:基于小波的粒子群数字图像水印优化算法

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摘要

Digital watermarking techniques have been proposed for copyright protection and multimedia data authentication. The achieved tradeoffs from these techniques between imperceptibility and robustness are always controversial. This paper proposes the application of Discrete Wavelet Transform (DWT) into image watermarking by using Particle Swarm Optimization (PSO) which is an evolutionary technique with the stochastic, population-based algorithm for solving this problem. To protect copyright information of digital images, the original image is decomposed according to two-dimensional discrete wavelet transform. Subsequently the preprocessed watermark with an affined scrambling transform is optimal embedded into the vertical subband (HL_m) coefficients in wavelet domain without compromising the quality of the image. In the optimal process, the scaling factors are trained with the assistance of PSO. Furthermore, a novel algorithmic framework is proposed via a forecasted feasibility of the approach to parameters evaluation of hypothesized watermarked images in DWT domain. Simulation results show that the proposed watermarking procedure has better performances in imperceptibility and robustness under various distortions in the comparison of the previous scheme.
机译:已经提出了用于版权保护和多媒体数据认证的数字水印技术。这些技术在不可感知性和鲁棒性之间取得的权衡始终是有争议的。本文提出了离散小波变换(DWT)在图像水印中的应用,它是一种采用基于种群的随机,随机算法的进化技术粒子群优化(PSO)。为了保护数字图像的版权信息,根据二维离散小波变换对原始图像进行分解。随后,在不影响图像质量的前提下,将经过有限扰动变换的预处理水印最优嵌入小波域的垂直子带(HL_m)系数中。在最佳过程中,在PSO的帮助下缩放比例因子。此外,通过预测DWT域中假设水印图像参数评估方法的可行性,提出了一种新颖的算法框架。仿真结果表明,与现有方案相比,该算法在各种失真下的不感知性和鲁棒性都有较好的表现。

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