Method and system for large-capacity image steganography and recovery based on invertible neural networks

A method for large-capacity image steganography based on an invertible neural networks, wherein the method for large-capacity image steganography is implemented based on the invertible neural networks, the invertible neural networks comprises invertible modules, the invertible module comprises a host branch and a hidden branch, and the method for large-capacity image steganography comprises:

• inputting a host image and a hidden image;
• embedding feature information of the hidden image into the host image through forward mapping of the invertible neural networks;
• forwardly outputting a stego image by utilizing the host branch of the invertible neural networks, wherein the stego image is an image obtained by embedding the feature information of the hidden image into the host image;
• and
• forwardly outputting a constant matrix by utilizing the hidden branch of the invertible neural networks, wherein the constant matrix does not contain effective information of the hidden image.

A system for large-capacity image steganography based on an invertible neural networks, wherein the system for large-capacity image steganography is implemented based on the invertible neural networks, the invertible neural networks comprises invertible modules, and the invertible module comprises a host branch and a hidden branch, the system for large-capacity image steganography comprising:

• an input module, configured to input a host image and a hidden image;
• an information embedding module, configured to embed feature information of the hidden image into the host image through forward mapping of the invertible neural networks;
• a stego image output module, configured to forwardly output a stego image by utilizing the host branch of the invertible neural networks, wherein the stego image is an image obtained by embedding the feature information of the hidden image into the host image;
• and
• a constant matrix output module, configured to forwardly output a constant matrix by utilizing the hidden branch of the invertible neural networks, wherein the constant matrix does not contain effective information of the hidden image.