Robust image watermarking based on generative adversarial network

Abstract

Digital watermark embeds information bits into digital cover such as images and videos to prove the creator's ownership of his work. In this paper, we propose a robust image watermark algorithm based on a generative adversarial network. This model includes two modules, generator and adversary. Generator is mainly used to generate images embedded with watermark, and decode the image damaged by noise to obtain the watermark. Adversary is used to discriminate whether the image is embedded with watermark and damage the image by noise. Based on the model Hidden (hiding data with deep networks), we add a high-pass filter in front of the discriminator, making the watermark tend to be embedded in the mid-frequency region of the image. Since the human visual system pays more attention to the central area of the image, we give a higher weight to the image center region, and a lower weight to the edge region when calculating the loss between cover and embedded image. The watermarked image obtained by this scheme has a better visual performance. Experimental results show that the proposed architecture is more robust against noise interference compared with the state-of-art schemes.