Abstract: The purpose of image hiding is to hide the secret image in the cover image,so that the secret image is still imperceptible to the human eyes,but can be restored when needed.Previous image hiding methods were limited in terms of hiding ability and robustness,and they are often susceptible to distortion in transmission.So,this paper proposes a model called RIHIGAN.It uses the same network through forward and backward processes to achieve image hiding and restoration.In the invertible network module,the models image reconstruction ability is enhanced by combining attention mechanisms.On the basis of reversible networks,the architecture of generative adversarial networks is introduced.At the same time,the structure of the discriminator has been improved by combining residual blocks to enhance its discrimination ability. The experiments results show that RIHIGAN effectively enhances robustness while maintaining recovery rate and invisibility.

Key words: image hiding, information hiding, deep learning, invertible network, generative adversarial network, robustness