Digital image watermarking is the process of embedding and extracting a
watermark covertly on a cover-image. To dynamically adapt image watermarking
algorithms, deep learning-based image watermarking schemes have attracted
increased attention during recent years. However, existing deep learning-based
watermarking methods neither fully apply the fitting ability to learn and
automate the embedding and extracting algorithms, nor achieve the properties of
robustness and blindness simultaneously. In this paper, a robust and blind
image watermarking scheme based on deep learning neural networks is proposed.
To minimize the requirement of domain knowledge, the fitting ability of deep
neural networks is exploited to learn and generalize an automated image
watermarking algorithm. A deep learning architecture is specially designed for
image watermarking tasks, which will be trained in an unsupervised manner to
avoid human intervention and annotation. To facilitate flexible applications,
the robustness of the proposed scheme is achieved without requiring any prior
knowledge or adversarial examples of possible attacks. A challenging case of
watermark extraction from phone camera-captured images demonstrates the
robustness and practicality of the proposal. The experiments, evaluation, and
application cases confirm the superiority of the proposed scheme.

本文提出了一种基于深度学习神经网络的鲁棒盲水印方案，该方案实现了自适应图像水印算法，无需人工干预和注释，并且不需要事先了解敌对攻击的有关信息，实验证明了该方案的优越性。

一种基于深度神经网络的自动、高效和健壮的图像水印方案

An Automated and Robust Image Watermarking Scheme Based on Deep Neural  Networks

This paper presents a hybrid digital image watermarking based on Discrete
Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value
Decomposition (SVD) in a zigzag order. From DWT we choose the high band to
embed the watermark that facilities to add more information, gives more
invisibility and robustness against some attacks. Such as geometric attack.
Zigzag method is applied to map DCT coefficients into four quadrants that
represent low, mid and high bands. Finally, SVD is applied to each quadrant.

本文介绍了一种基于离散小波变换（DWT）、离散余弦变换（DCT）和奇异值分解（SVD）的混合数字图像水印技术，其中采用了 zigzag 算法。通过使用 DWT 的高频带来嵌入水印以添加更多信息、提高对某些攻击的鲁棒性，最后将 zigzag 算法应用于将 DCT 系数映射到四个象限，从而获得更好的效果。最后，对每个象限应用 SVD。