The crucial hurdle faced by the watermarking technique is to maintain the steadiness corresponding to several attacks while assisting a sufficient level of security. In this study, a robust lossless sparse domain-based watermarking approach combined with discrete cosine transform (DCT) is introduced to hide the secret message in the selected significant sparse elements of the host image. The proposed method takes advantage of a sparse representation-based dictionary learning process. To enhance the security of the original image, the authors first apply the DCT on a secret message. These DCT coefficients with some regularised parameters will be inserted into the selected significant sparse coefficients. At the extraction stage, the secret message is extracted from those significant sparse coefficients by employing the sparse domain orthogonal matching pursuit algorithm. Finally, the inverse DCT is applied to extract the secret message without any information loss. To show the effectiveness of the proposed method, different commonly used attacks are simulated. Simulation results in terms of peak signal-to-noise ratio, structural similarity, normal correlation, and feature similarity indicate that the proposed method can recover the hidden secret message accurately against seven different types of attacks including speckle, Gaussian, salt and pepper, rotate, crop, fold, and blur attack.

中文翻译：

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基于K奇异值分解算法的稀疏域无损数字图像水印

加水印技术面临的关键障碍是维持与几种攻击相对应的稳定性，同时协助提供足够的安全级别。在这项研究中，引入了结合离散余弦变换（DCT）的鲁棒的基于无损稀疏域的水印方法，以将秘密消息隐藏在选定的主机图像的重要稀疏元素中。所提出的方法利用了基于稀疏表示的字典学习过程。为了增强原始图像的安全性，作者首先在秘密消息上应用了DCT。这些带有某些正则化参数的DCT系数将插入到选定的有效稀疏系数中。在提取阶段 通过采用稀疏域正交匹配追踪算法，从那些重要的稀疏系数中提取秘密消息。最终，逆DCT被应用于提取秘密消息而没有任何信息丢失。为了显示所提出方法的有效性，模拟了不同的常用攻击。从峰值信噪比，结构相似性，正态相关性和特征相似性方面的仿真结果表明，所提出的方法能够针对斑点，高斯，盐和胡椒等七种不同类型的攻击准确地恢复隐藏的秘密消息，并进行旋转，裁剪，折叠和模糊攻击。模拟了不同的常用攻击。从峰值信噪比，结构相似性，正态相关性和特征相似性方面的仿真结果表明，所提出的方法能够针对斑点，高斯，盐和胡椒等七种不同类型的攻击准确地恢复隐藏的秘密消息，并进行旋转，裁剪，折叠和模糊攻击。模拟了不同的常用攻击。从峰值信噪比，结构相似性，正态相关性和特征相似性方面的仿真结果表明，所提出的方法能够针对斑点，高斯，盐和胡椒等七种不同类型的攻击准确地恢复隐藏的秘密消息，并进行旋转，裁剪，折叠和模糊攻击。