Diffusion Denoising Watermark Removal Models to Attack Invisible Image Watermarks

Imperceptible image watermarking methods strive to balance visibility with robustness requirements in order to protect copyright images from copyright infringement without impacting users’ viewing experience. Additionally, image generators such as Stable Diffusion and Google’s Imagen utilize watermarking to enable the detection of synthetically generated images. To guarantee a sufficient level of robustness, watermarking methods are evaluated against traditional attacks. We recognize diffusion models as a potential disruptive technology in the watermark robustness field and therefore investigate this approach. This paper presents Diffusion Denoising Watermark Removal Models (DDWRM) as a watermark attack. Instead of generating images from noise, our approach strategically diffuses watermarked images, followed by a denoising process to effectively remove embedded watermarks while preserving the original content. The methodology is designed to be generic, showcasing its potential as a robust and versatile watermark removal technique. Experimental results highlight the proposed DDWRM’s success in removing watermarking information, outperforming the traditional JPEG compression attack method for specific watermarking techniques (DWT-DCT-SVD and Riva-GAN). However, variations in resilience, particularly with DWT-DCT watermarking method, prompt further exploration needs. In conclusion, our proposed attack emerges as an innovative and effective watermark removal method.