DoBMark: A double-branch network for screen-shooting resilient image watermarking

被引:11
作者
Guo, Daidou [1 ]
Zhu, Xuan [1 ]
Li, Fengyong [2 ]
Yao, Heng [1 ]
Qin, Chuan [1 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai 200093, Peoples R China
[2] Shanghai Univ Elect Power, Coll Comp Sci & Technol, Shanghai 200090, Peoples R China
基金
上海市自然科学基金; 中国国家自然科学基金;
关键词
Robust watermarking; Screen-shooting; JND constraint; Alternate-fusion mechanism; SIGNAL COMPRESSION;
D O I
10.1016/j.eswa.2024.123159
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The dramatic changes in cross -media information transmission modes, especially screen -shooting, have made traditional robust image watermarking for digital channels less resistant to various physical noises from the real world. To address this problem, we propose a double -branch network for screen -shooting resilient image watermarking. Specifically, two weights conforming to a Gaussian distribution are assigned to the doublebranch encoder, and by jointly training, two residual images containing watermark information are produced to generate the fused watermarked image. A dual frame alternate -fusion mechanism and a just noticeable difference (JND) constraint function on residual images are employed to improve the watermark invisibility and the quality of watermarked images. A differentiable distortion network is introduced to enhance the robustness of the end -to -end network. Additionally, the decoder integrates a quality enhancement module (QEM) that can correct distortions and apply de -noising to the distorted images, thereby improving the accuracy of watermark information extraction. Experimental results show that the proposed scheme can achieve high robustness against the screen -shooting process while maintaining a satisfactory watermark capacity and visual quality of the watermarked image.
引用
收藏
页数:13
相关论文
共 43 条
[1]   ReDMark: Framework for residual diffusion watermarking based on deep networks [J].
Ahmadi, Mahdi ;
Norouzi, Alireza ;
Karimi, Nader ;
Samavi, Shadrokh ;
Emami, Ali .
EXPERT SYSTEMS WITH APPLICATIONS, 2020, 146
[2]  
Anwar S, 2020, Arxiv, DOI [arXiv:1904.07396, DOI 10.48550/ARXIV.1904.07396]
[3]  
Arjovsky M, 2017, PR MACH LEARN RES, V70
[4]   SSDeN: Framework for Screen-Shooting Resilient Watermarking via Deep Networks in the Frequency Domain [J].
Bai, Rui ;
Li, Li ;
Zhang, Shanqing ;
Lu, Jianfeng ;
Chang, Chin-Chen .
APPLIED SCIENCES-BASEL, 2022, 12 (19)
[5]   Screen-shooting resistant image watermarking based on lightweight neural network in frequency domain [J].
Cao, Fang ;
Wang, Tianjun ;
Guo, Daidou ;
Li, Jian ;
Qin, Chuan .
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2023, 94
[6]  
Cheng YS, 2021, PROCEEDINGS OF THE 30TH USENIX SECURITY SYMPOSIUM, P2969
[7]   A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile [J].
Chou, CH ;
Li, YC .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 1995, 5 (06) :467-476
[8]  
Cui H, 2019, IEEE INFOCOM SER, P1315, DOI [10.1109/infocom.2019.8737627, 10.1109/INFOCOM.2019.8737627]
[9]   An SVD-based screen-shooting resilient watermarking scheme [J].
Deng, Biao ;
Li, Sheng ;
Qian, Zhenxing .
MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (23) :32841-32855
[10]  
Deng J, 2009, PROC CVPR IEEE, P248, DOI 10.1109/CVPRW.2009.5206848