A Secret Image Sharing Method Based on Shared Matrix and Variational Hyperprior Network

At present people can easily share multimedia information on Internet, which leads to serious data security issues. Especially in medical, military and financial fields, images always contain a lot of sensitive information. To safely transmit images among people, many secret image sharing methods are proposed. However, the existing methods can not solve the problems of pixel expansion and high computational complexity of shadow images at the same time. In this paper, we propose an image sharing method by combining sharing matrix and variational hyperprior network, to reduce the pixel expansion and computational complexity of secret image sharing methods. The method uses the variational hyperprior network to encode images. It introduces the hyperprior to effectively catch spatial dependencies in the latent representation, which can compress image with high efficiency. The experimental results show that our method has low computational complexity and high security performance compared with the state-of-the-art approaches. In addition, the proposed method can effectively reduce the pixel expansion when using the sharing matrix to generate shadow images.