Deep Boosting Robustness of DNN-Based Image Watermarking via Dbmark

Guanhui Ye1; Jiashi Gao1; Bo Yin2; Wei Xie3; Xuetao Wei1

10.1109/CoST60524.2023.00046

2023

2023 International Conference on Culture-Oriented Science and Technology (CoST)

979-8-3503-5800-1

2023 International Conference on Culture-Oriented Science and Technology (CoST)

186-191

11-14 Oct. 2023

Xi’an, China

Image watermarking is a technique for hiding information into images that can withstand distortions while requiring the encoded image to be perceptually identical to the original image. Recent work based on deep neural networks (DNN) has achieved impressive progression in digital watermarking. Higher robustness under various distortions is the eternal pursuit of digital image watermarking approaches. In this paper, we propose DB MARK, a novel end-to-end digital image watermarking framework to deep boost the robustness of DNN-based image watermarking. The key novelty is the synergy of invertible neural networks (INN) and effective watermark features generation. The framework generates watermark features with redundancy and error correction ability through the effective neural network based message processor, synergized with the powerful information embedding and extraction abilities of INN to achieve higher robustness and invisibility. The powerful learning ability of neural networks enables the message processor to adapt to various distortions. In addition, we propose to embed the watermark information in the discrete wavelet transform (DWT) domain and design low-low $(LL)$ sub-band loss to enhance invisibility. Extensive experiment results demonstrate the superiority of the proposed framework compared with the state-of-the-art ones under various distortions such as dropout, cropout, crop, Gaussian filter, and JPEG compression.

Image Watermarking Video Watermarking Convolutional Neural Networks Robustness Invisibility

第一 ; 通讯

EI

20240215337815

Convolutional Neural Networks ; Deep Neural Networks ; Discrete Wavelet Transforms ; Error Correction ; Image Compression

Ergonomics And Human Factors Engineering:461.4 ; Data Processing And Image Processing:723.2 ; Mathematical Transformations:921.3

IEEE

1.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
2.School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, China
3.School of Journalism and Communication, Hunan University, Changsha, China

Guanhui Ye,Jiashi Gao,Bo Yin,et al. Deep Boosting Robustness of DNN-Based Image Watermarking via Dbmark[C],2023:186-191.