Hide the Image in FC-DenseNets to another Image

TL;DR

This paper introduces a neural network-based steganography method using FC-DenseNet that achieves high-capacity image hiding with good visual quality and effective secret image extraction.

Contribution

We propose a novel steganography approach based on FC-DenseNet that enhances capacity while maintaining image quality and allows full-size image hiding.

Findings

High steganographic capacity achieved

Stego-images maintain good visual quality

Effective secret image extraction from stego-images

Abstract

In the past, steganography was to embed text in a carrier, the sender Alice and the recipient Bob share the key, and the text is extracted by Bob through the key. If more information is embedded, the image is easily distorted. In contrast, if there is less embedded information, the image maintains good visual integrity, but does not meet our requirements for steganographic capacity. In this paper, we focus on tackling these challenges and limitations to improve steganographic capacity. An image steganography method based on Fully Convolutional Dense Network(FC-DenseNet) was proposed by us. The hidden network and the extracted network are trained at the same time. The dataset of the deep neural network is derived from various natural images of ImageNet. The experimental results show that the stego-image after steganography and the secret image extracted from stego-imge have a visually good effect, and the stego-image has high capacity and high peak signal to noise ratio. Image-to-image full size hiding is implemented.