[1]JIANG Hao,YAO Yuhan,WANG Jiahao,et al.Pyramid-enhanced noise-resilient watermarking for robust and high-quality image protection[J].CAAI Transactions on Intelligent Systems,2026,21(1):72-82.[doi:10.11992/tis.202507022]
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Pyramid-enhanced noise-resilient watermarking for robust and high-quality image protection

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 21 Number of periods: 2026 1 Page number: 72-82 Column: 学术论文—机器学习 Public date: 2026-03-05
Title:
Pyramid-enhanced noise-resilient watermarking for robust and high-quality image protection
Author(s):
JIANG Hao1;  YAO Yuhan2;  WANG Jiahao2;  LI Xingchen2;  WANG Dingke2;  TANG Xinkun1;  LI Juntao3;  KOU Feifei2
1. Academy of Broadcasting Science, National Radio and Television Administration, Beijing 100866, China;
2. School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing 100876, China;
3. School of Information, Beijing Wuzi University, Beijing 101149, China
Keywords:
blind watermarking; information hiding; copyright protection; multi-scale features; robustness; noise attacks; end-to-end learning; deep watermarking
CLC:
TP391.4
DOI:
10.11992/tis.202507022
Abstract:
To address the widespread issue of unauthorized reuse of images in digital media, robust blind watermarking is essential. However, existing methods struggle to simultaneously withstand real-world noise attacks while maintaining high extraction accuracy and excellent visual quality. To this end, we propose Pyramid-Enhanced Noise-Resilient Watermarking (PENRW), which leverages pyramid-based multi-scale feature embedding and a watermark-decoding quality enhancement module to achieve highly accurate watermark extraction under strong noise with minimal image quality degradation. Experiments demonstrate that our method surpasses current state-of-the-art approaches in both robustness and visual fidelity.
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