High-Capacity Information Hiding Based On Residual Network

To solve the problem of the low capacity of traditional information hiding and steganography, the deep neural network is used to construct a hidden network and a decoding network to hide one image into another. In this paper, the ResNet (Residual Network) has a good effect in feature extraction, and the residual block is used in the hidden network. First, the hidden network encoded the secret image into cover image. During the encoding process, the steganography image mimics the distribution of the cover image as much as possible. Then, the receiver sends the steganography image to the decoding network to obtain the secret image. Experimental results indicate that the scheme will solve the obvious problems of visual cues, also improve the ability of embedding.