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, Yunqing Shi
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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 intraprediction modes (IPMs) of 4x4 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. Experiments 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.
Chairs:
Rémi Cogranne