The existing image steganography methods either sequentially conceal secret images or conceal a concatenation of multiple images. In such ways, the interference of information among multiple images will become increasingly severe when the number of secret images becomes larger, thus restrict the development of very large capacity image steganography. In this paper, we propose an Invertible Mosaic Image Hiding Network (InvMIHNet) which realizes very large capacity image steganography with high quality by concealing a single mosaic secret image. InvMIHNet consists of an Invertible Image Rescaling (IIR) module and an Invertible Image Hiding (IIH) module. The IIR module works for downscaling the single mosaic secret image form by spatially splicing the multiple secret images, and the IIH module then conceal this mosaic image under the cover image. The proposed InvMIHNet successfully conceal and reveal up to 16 secret images with a small number of parameters and memory consumption. Extensive experiments on ImageNet-1K, COCO and DIV2K show InvMIHNet outperforms state-of-the-art methods in terms of both the imperceptibility of stego image and recover accuracy of secret image.

翻译：现有的图像隐写方法要么依次隐藏秘密图像，要么隐藏多个图像的拼接结果。以这种方式，当秘密图像数量增大时，多幅图像之间的信息干扰会愈发严重，从而限制了大容量图像隐写的发展。本文提出了一种可逆马赛克图像隐藏网络（InvMIHNet），通过隐藏单幅马赛克秘密图像实现高质量的大容量图像隐写。InvMIHNet包含可逆图像缩放模块（IIR）和可逆图像隐藏模块（IIH）。IIR模块负责对由多幅秘密图像空间拼接而成的单幅马赛克秘密图像进行下采样，随后IIH模块将该马赛克图像隐藏在载体图像下。所提出的InvMIHNet能以较少的参数和内存消耗成功隐藏并恢复多达16幅秘密图像。在ImageNet-1K、COCO和DIV2K数据集上的大量实验表明，InvMIHNet在隐写图像的不可感知性和秘密图像的恢复精度方面均优于现有最先进方法。