Efficient image encryption and compression based on a VAE generative model

Efficient image encryption and compression not only well protect the security of image information, but also greatly reduce the bandwidth. This paper proposes an image encryption method based on variational auto-encoder generation model. Firstly, we use the random gradient method to train the variational auto-encoder generation model, and iteration times of the model is determined comprehensively by the training time, the loss function and the reconstruction image. The peak signal-to-noise ratio and mean square error are used to measure the compression effect of the model. Secondly, we utilize the two trained image data divisions to change the data of the generated model, and to generate an encryption image. Finally, this paper uses Spyder to simulate experiments and analyze the results. The experimental results show that the method is fast and easy to encrypt, the algorithm is simple and the distortion rate of the decrypt image is low, and it is strong practicality.