RMIT University
Browse

Fast watermarking scheme for real-time spatial scalable video coding

journal contribution
posted on 2024-11-03, 13:10 authored by Adamu Buhari, Huo Chong LingHuo Chong Ling, Vishnu Baskaran, KokSheik Wong
Recent advancements in high resolution scalable video coding have significantly increased the computational complexities of watermarking solutions for real-time video encoding systems. This paper proposes a human visual system based watermarking algorithm for spatial scalable coding based on the H.264/SVC standard. The proposed algorithm extracts textural feature from a set of 7 high energy quantized coefficients in 4×4 luma INTRA-predicted blocks of all slices and embeds watermark into the highly textured block which has at least one non-zero coefficient in 6 selected locations. The same embedding process is performed for all layers of the video to improve robustness against common video processing attacks. Experiments were conducted by embedding up to 8192 watermark bits into a four-layer spatial scalable coded video. Results suggest that the proposed scheme produces watermarked video with an average visual quality degradation of ∼0.36 dB at the expense of 2.18% bitrate overhead. In addition, the proposed watermarking scheme achieves an average detection rate of 0.98, 0.97 and 0.71 against re-encoding, recompression and Gaussian filtering attacks, respectively, using the base layer, and above 0.97, 0.94 and 0.66, respectively when using any of the enhancement layer.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.image.2016.06.003
  2. 2.
    ISSN - Is published in 09235965

Journal

Signal Processing: Image Communication

Volume

47

Start page

86

End page

95

Total pages

10

Publisher

Elsevier BV

Place published

Netherlands

Language

English

Copyright

© 2016 Elsevier B.V. All rights reserved.

Former Identifier

2006127049

Esploro creation date

2023-11-30

Usage metrics

    Scholarly Works

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC