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A High Capacity HEVC Steganographic Algorithm Using Intra Prediction Modes in Multi-sized Prediction Blocks

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Digital Forensics and Watermarking (IWDW 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11378))

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Abstract

The existing video steganographic schemes based on intra prediction modes for video coding standards H.264/AVC and HEVC all use single-sized blocks to embed the secret payload. Thus, the steganographic properties of HEVC multi-sized tree-structured intra partition still need exploration. In this paper, a novel video steganographic algorithm is presented. Base on the fact that visual quality degradation caused by steganography is basically the same for both large-sized Prediction Blocks (PBs) and small-sized PBs, this algorithm tries to exploit intra prediction modes in multi-sized PBs in each Coding Tree Units (CTU). The innovation of this paper includes: (1) Improvement in capacity without introducing great degradation in visual quality. (2) High coding efficiency maintained by defining cost function based on rate distortion. (3) A new indicator to measure Bit Increase Ratio(BIR) under different capacity. The Experimental results show that this algorithm outperforms the latest intra prediction modes based HEVC steganographic algorithm in both capacity and perceptibility while preserving coding efficiency as well.

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Acknowledgement

This work is supported by the National Natural Science Foundation of China (No. 61572320, 61572321). Corresponding author is Professor Xinghao Jiang, any comments should be addressed to xhjiang@sjtu.edu.cn.

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Dong, Y., Sun, T., Jiang, X. (2019). A High Capacity HEVC Steganographic Algorithm Using Intra Prediction Modes in Multi-sized Prediction Blocks. In: Yoo, C., Shi, YQ., Kim, H., Piva, A., Kim, G. (eds) Digital Forensics and Watermarking. IWDW 2018. Lecture Notes in Computer Science(), vol 11378. Springer, Cham. https://doi.org/10.1007/978-3-030-11389-6_18

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  • DOI: https://doi.org/10.1007/978-3-030-11389-6_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11388-9

  • Online ISBN: 978-3-030-11389-6

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