High-capacity and high-security color image hiding based on generative pixel shuffle residual-CNN

Image hiding is the technique of embedding secret information into a carrier in a covert manner to ensure secure transmission of information. Traditional image hiding has insufficient resistance to the latest steganalysis tool based on deep learning and has low robustness. In addition, current image hiding models have relatively lower hiding capacity and mostly only hide gray images. This paper proposed steganography based on generative pixel shuffle residual network (GPRS-Net), that is capable of hiding single or multi color secret images in a carrier image. The secret image is decomposed and encoded into different feature maps using a preprocessing network, which allows the GPRS-Net to better fuse the secret information into the carrier image, thus enabling the output of the stego image. Subsequently, a deep recovery network based on residual module and pixel shuffling module is constructed, with the aim of potentially recovering the secret image with less loss from the attacked stego image, thus improving robustness and security. Experiments show that the proposed GPRS-Net has excellent performance in terms of hidden capacity and security.