Image-to-Image Steganography Using Encoder-Decoder Network

Abstract

In this paper, a convolution neural network is utilized for image-to-image steganography using encoder decoder architecture. A new loss function is designed to improve the invisibility of payload image. The encoder-decoder architecture is used for the image-to-image steganography. The developed architecture is evaluated on the well-known image dataset and compared with the recently developed models. The proposed model was able to withstand the stegoanalyzer attack and better visual quality of stego image. It is able to achieve great imperceptibility.