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收稿：2017-06-26，
修回：2017-10-17，
纸质出版：2018-02-16
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目的
2
以运动矢量（MV）为载体的视频隐写算法会破坏同一帧内相邻宏块或者相邻帧相同位置宏块的运动矢量之间的相关性，从而容易被基于运动矢量时空相关性（temporal-spatial correlation）特征的隐写分析算法检测到。为了解决这个问题，在H.264/AVC的视频编解码标准下构建了一种能抵抗基于运动矢量时空相关性隐写分析的视频隐算法。
方法
2
通过分析运动矢量残差（MVD）与运动矢量时空相关性的联系，证明了保持运动矢量残差的统计特征的隐写算法能够很好地保持视频运动矢量的时空相关性；通过分析运动矢量残差的统计特征设置了一种能保持其直方图特征的嵌入规则，使用4个标记符和一个队列来记录修改载体造成的特征改变，并进行相应的补偿操作，将秘密信息嵌入到视频压缩过程中的熵编码之前的运动矢量残差中；结合可变长度的矩阵编码，有效降低了嵌入秘密信息对载体的修改量。
结果
2
实验结果表明，该算法能较好地保持运动矢量残差在隐写前后的直方图特征，具有较好的视觉不可见性，对视频峰值信噪比（PSNR）和码率影响都不超过0.5%，满载嵌入的情况下基于运动矢量时空相关性的隐写分析算法对其的检测正确率只有70%左右。
结论
2
本文算法以运动矢量残差为隐写嵌入的载体，使用保持其直方图特征的嵌入规则，结合了矩阵编码以减低对载体的修改量，能较好抵抗基于运动矢量时空相关性的隐写分析。
Objective
2
Numerous video encoding standards commonly acquire encoding data through intra-and inter-frame predictions
which use encoded information to predict the data to be encoded. Thus
the temporal-spatial correlation between data is a common phenomenon between the motion vectors (MV) of adjacent macroblocks in the same frame or the macroblocks in the same position of the adjacent frames. Steganography algorithms that are based on MV typically change the value of MV selectively to embed confidential information. The change may damage the correlation between the MVs of adjacent macroblocks in the same frame or the macroblocks in the same position of the adjacent frames. Consequently
these algorithms could be easily detected by steganalysis algorithms based on MV temporal-spatial correlations. A video steganography algorithm that can resist the steganalysis algorithms based on the temporal-spatial correlations of MVs is proposed with the video-encoding standard guideline of H.264/AVC to solve the abovementioned problem.
Method
2
This paper deduces the correlation between MV difference (MVD) and temporal-spatial correlations of MVs to verify that maintaining the statistical features of the MVD is helpful for maintaining the temporal-spatial correlations of the video MVs by analyzing the calculation theorems of the MVD and temporal-spatial correlations of MVs. The proposed method develops an embedding rule
which could retain the features of the histogram related to the MVD because the statistical histogram of MVD is consistent with the Laplace distribution. This rule uses four counters and a queue to record the change in features caused by the modifying carriers
while compensation operations are conducted to recover statistical features to embed the secret messages into the MVDs before the entropy coding in the video compression process. To further decrease the modification of carriers related to embedding confidential information
matrix coding with variable length is applied according to various macroblock partitions to embed multiple bits of confidential information with only one bit of carriers that are modified.
Result
2
Three experiments were conducted in this study. First
the confidential information embedding and extraction experiment were conducted. Experimental results show that the steganography algorithm can effectively and correctly complete the embedding and extraction of confidential information
and the accurate rate of multi-group experiments are all 100%. Then
the experiment for determining the influence of the algorithm on the statistics characteristics of video sequences was conducted. In this experiment
the proposed and other previous algorithms were used to embed confidential information in the case of full load embedding. Experimental results also show that the proposed steganography algorithm has visual invisibility and has a modification of less than 0.5% on the peak signal-to-noise ratio (PSNR) and the bit rate of the videos after embedding information. Finally
the resisting steganalysis algorithm experiment was conducted. The proposed and other previous algorithms were used to embed confidential information with various embedding rates
and then extract feature values from the video sequences. The steganalysis algorithms based on the temporal-spatial correlations of motion vectors were used to detect the feature values. Compared with previous steganography algorithms based on MVs
the proposed algorithms can maintain the histogram feature of MVDs before and after secret information is embedded. The use of matrix coding with variable length leads to a considerable decrease in the influence of steganography on the video sequence features
and the detection accuracy of steganalysis algorithms based on the temporal-spatial correlations of MVs on the proposed algorithm in this paper is only approximately 70%.
Conclusion
2
Our algorithm uses the MVD as the carrier of steganography while using the embedding rule
which could retain the statistics histogram features. Moreover
matrix coding with variable length is used to decrease the modification of steganography on carriers. Overall
the proposed algorithm can effectively and accurately complete the embedding and extraction of confidential information
minimally modify the PSNR and bit rate of videos
and significantly produce favorable performance when facing steganography algorithms based on MV temporal-spatial correlations.
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