摘要
Deep neural network has proven to be very effective in computer vision fields.Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods.Generative adversarial network(GAN)is becoming one of the highlights among these deep neural networks.GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks.One promising application of using GAN generated images would be image concealing which requires the embedded image looks like not being tampered to human vision system and also undetectable to most analyzers.Texture synthesizing has drawn lots of attention in computer vision field and is used for image concealing in steganography and watermark.The traditional methods which use synthesized textures for information hiding mainly select features and mathematic functions by human metrics and usually have a low embedding rate.This paper takes advantage of the generative network and proposes an approach for synthesizing complex texture-like image of arbitrary size using a modified deep convolutional generative adversarial network(DCGAN),and then demonstrates the feasibility of embedding another image inside the generated texture while the difference between the two images is nearly invisible to the human eyes.
基金
This work is supported by the National Key R&D Program of China under grant 2018YFB1003205
by the National Natural Science Foundation of China under grant U1536206,U1405254,61772283,61602253,61672294,61502242
by the Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20150925 and BK20151530
by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund
by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China.
