Image Hiding Method Based on Two-Channel DeepConvolutional Neural Network

The existing image information hiding methods based on Deep Convolutional Neural Networks (DCNN) have the problems of poor image visual quality and low hiding capacity. Addressing such issues, an image hiding method based on a two-channel deep convolutional neural network is proposed. First, different from the previous hiding framework, the hiding method proposed in this paper includes one hiding network and two revealing networks with the same structure, and two full-size secret images can be effectively hidden and revealed at the same time is realized. Then, to improve the visual quality of the image, an improved pyramid pooling module and a preprocessing module are added to the hiding and revealing network. The test results on multiple data sets show that the proposed method has a significant improvement in visual quality compared with existing image information hiding methods. The Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) values are increased by 3.75 dB and 3.61 % respectively, a relative capacity of 2 and good generalization ability are achieved.