Abstract
HEVC video is one of the most popular carriers for steganography. The existing transform coefficient-based HEVC steganography algorithms usually modify the coefficients of the candidate blocks to prevent distortion drift. Nevertheless, the embedding capacity is relatively small due to the strict candidate block selection rule, and embedding distortion is accumulated within group of pictures (GOP). In this paper, a novel transform coefficient-based steganography for HEVC is proposed to enlarge embedding capacity and reduce visual degradation. First, the visual distortion and GOP distortion are analyzed to elaborate the embedding influence of different cover coefficients. Next, different cover coefficients are assigned different costs. Besides, the modification in non-zero coefficients of \(4\times 4\) TUs in P-frames is explored to enhance embedding capacity. Moreover, by introducing a new evaluation indicator, it is verified the proposed algorithm can preserve less visual degradation while embedding more secret messages. Experimental results show that the proposed algorithm outperforms the competing methods in terms of visual quality, embedding capacity and anti-steganalysis performance.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (62071267, 61771270, 62171244), Zhejiang Provincial Natural Science Foundation of China (LR20F020001).
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Yang, L., Wang, R., Xu, D., Dong, L., He, S., Liu, F. (2023). High-Capacity Adaptive Steganography Based on Transform Coefficient for HEVC. In: Zhao, X., Tang, Z., Comesaña-Alfaro, P., Piva, A. (eds) Digital Forensics and Watermarking. IWDW 2022. Lecture Notes in Computer Science, vol 13825. Springer, Cham. https://doi.org/10.1007/978-3-031-25115-3_2
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