基于溢出抑制的抖动调制鲁棒隐写算法
Improving Dither Modulation based Robust Steganography by Overflow Suppression
摘要：
如今，人们在在线社交网络（OSN）上分享他们的照片，所以OSN是一个很好的隐写平台。但OSN通常对上传的图像进行JPEG压缩，这将使大多数现有的隐写算法失效。近年来，一些研究工作试图设计抗JPEG压缩的鲁棒隐写算法，如基于抖动调制的鲁棒自适应隐写（DMAS）和基于广义抖动调制的鲁棒自适应隐写（GMAS）。该算法解决了信道JPEG压缩质量因子大于封面图像质量因子时，接收端不能正确提取信息的问题。然而，由于鲁棒的域选择，它们只能实现有限的抵抗检测和压缩。为了克服这个问题，我们仔细研究了JPEG再压缩中的三种有损操作，发现其关键问题是空间溢出。然后提出了全局缩放和特定截断两种预处理方法，用于在消息嵌入前消除溢出并生成参考图像。在嵌入过程中，以参考图像为指导建立非对称失真，以消除溢出。实验结果表明，所提出的方法显着优于GMAS的安全性和实现可比的鲁棒性。
英文摘要：
Nowadays, people are sharing their pictures on online social networks (OSNs), so OSN is a good platform for Steganography. But OSNs usually perform JPEG compression on the uploaded image, which will invalidate most of the existing steganography algorithms. Recently, some works try to design robust steganography which can resist JPEG compression, such as Dither Modulation-based robust Adaptive Steganography (DMAS) and Generalized dither Modulation-based robust Adaptive Steganography (GMAS). They relieve the problem that the receivers cannot extract the message correctly when the quality factor of channel JPEG compression is larger than that of cover images. However, they only can realize limited resistance to detection and compression due to robust domain selection. To overcome this problem, we meticulously explore three lossy operations in the JPEG recompression and discover that the key problem is spatial overflow. Then two preprocessing methods Overall Scaling (OS) and Specific Truncation (ST) are presented to remove overflow before message embedding as well as generate a reference image. The reference image is employed as the guidance to build asymmetric distortion for removing overflow during embedding. Experimental results show that the proposed methods significantly surpass GMAS in terms of security and achieve comparable robustness.
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