A Layered Embedding-Based Scheme to Cope with Intra-Frame Distortion Drift In IPM-Based HEVC Steganography

Xiaoqing Jia, Jie Wang, Yongliang Liu, Xiangui Kang, Yun-Qing Shi
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Abstract

The spatial correlation of the intra-frame prediction units brings great challenges when minimizing embedding distortions using syndrome-trellis coding (STC) in High Efficiency Video Coding (HEVC) steganography. To solve this problem, we propose a layered embedding scheme which embeds information into the intra-prediction modes (IPMs) of 4×4 intra-frame prediction units (PUs) in HEVC. Firstly we divide the PUs of the intra-frame into different layers using Hasse diagram and make modification decisions for PUs in each layer respectively to decorrelate the correlated PUs. Secondly we make a statistics on more than 100,000 sampling PU pairs to quantitatively analyze the impacts between the distortions of PUs and then design a distortion function which takes mutual impacts of PUs into account. Experimental results show that our method can significantly reduce the embedding distortion and improve the security compared with the existing STC-based steganography methods embedding in IPMs.
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基于ipm的HEVC隐写中基于分层嵌入的帧内失真漂移处理方案
在高效视频编码(HEVC)隐写技术中,利用证格编码(STC)最小化嵌入失真时,帧内预测单元的空间相关性给减小嵌入失真带来了很大的挑战。为了解决这个问题,我们提出了一种分层嵌入方案,该方案将信息嵌入到HEVC中4×4帧内预测单元(pu)的内预测模式(ipm)中。首先利用Hasse图将帧内的pu划分为不同的层,并分别对每一层的pu进行修改决策,实现相关pu的去相关。其次,对10万多对采样PU对进行统计,定量分析PU之间的畸变影响,并设计考虑PU相互影响的畸变函数。实验结果表明,与现有的基于stc的ipm嵌入隐写方法相比,该方法可以显著降低嵌入失真,提高安全性。
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