论文标题
改善基于TCM的稳健隐肌的鲁棒性，可变鲁棒性
Improving Robustness of TCM-based Robust Steganography with Variable Robustness
论文作者
论文摘要
最近的研究发现，经过多次重新压缩，JPEG图像的DCT系数可以形成一个嵌入域，该结构域可重新压缩，这称为传输通道匹配（TCM）方法。由于自适应隐肌的成本函数并未考虑修饰对鲁棒性的影响，因此在重新压缩后TCM后，Stego图像的修饰DCT系数将发生变化。为了减少重新压缩后变化的系数的数量，本文提出了一种健壮的隐肌算法，该算法会动态更新每个DCT系数的稳健性成本。通过测试修改的DCT系数是否可以在STC嵌入过程的每个步骤中抵抗重新压缩来计算提出的鲁棒性成本。通过将稳健性成本添加到失真成本中，并使用STC嵌入算法嵌入消息的框架来嵌入消息，Stego图像在稳健性和安全性方面具有良好的性能。实验结果表明，所提出的算法可以显着增强Stego图像的鲁棒性，并且在使用较低质量因子重新压缩的情况下，几乎所有情况下都可以正确提取嵌入式消息，并且拟议算法的使用者知道了较低的质量因子。
Recent study has found out that after multiple times of recompression, the DCT coefficients of JPEG image can form an embedding domain that is robust to recompression, which is called transport channel matching (TCM) method. Because the cost function of the adaptive steganography does not consider the impact of modification on the robustness, the modified DCT coefficients of the stego image after TCM will change after recompression. To reduce the number of changed coefficients after recompression, this paper proposes a robust steganography algorithm which dynamically updates the robustness cost of every DCT coefficient. The robustness cost proposed is calculated by testing whether the modified DCT coefficient can resist recompression in every step of STC embedding process. By adding robustness cost to the distortion cost and using the framework of STC embedding algorithm to embed the message, the stego images have good performance both in robustness and security. The experimental results show that the proposed algorithm can significantly enhance the robustness of stego images, and the embedded messages could be extracted correctly at almost all cases when recompressing with a lower quality factor and recompression process is known to the user of proposed algorithm.
