Invisible watermarking is essential for safeguarding digital content, enabling copyright protection and content authentication. However, existing watermarking methods fall short in robustness against regeneration attacks. In this paper, we propose a novel method called FreqMark that involves unconstrained optimization of the image latent frequency space obtained after VAE encoding. Specifically, FreqMark embeds the watermark by optimizing the latent frequency space of the images and then extracts the watermark through a pre-trained image encoder. This optimization allows a flexible trade-off between image quality with watermark robustness and effectively resists regeneration attacks. Experimental results demonstrate that FreqMark offers significant advantages in image quality and robustness, permits flexible selection of the encoding bit number, and achieves a bit accuracy exceeding 90% when encoding a 48-bit hidden message under various attack scenarios.

翻译：隐形水印技术对于保护数字内容、实现版权保护与内容认证至关重要。然而，现有水印方法在抵抗再生攻击的鲁棒性方面存在不足。本文提出一种名为FreqMark的新方法，该方法通过对VAE编码后获得的图像潜在频率空间进行无约束优化来实现水印嵌入。具体而言，FreqMark通过优化图像的潜在频率空间来嵌入水印，并通过预训练的图像编码器提取水印。这种优化机制能够在图像质量与水印鲁棒性之间实现灵活权衡，并有效抵抗再生攻击。实验结果表明，FreqMark在图像质量和鲁棒性方面具有显著优势，允许灵活选择编码位数，并在多种攻击场景下编码48位隐藏信息时实现了超过90%的位准确率。