Improved wavelet-based watermarking through pixel-wise masking

By Mauro Barni, F. Bartolini, Alessandro Piva. IEEE Transactions on Image Processing, 2001

1,107 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/6fe33a4e2415e180a467d6507c7d86baae6ba8fb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Josef Kittler
2. Xiaojun Wu
3. Hui Li
4. Chia-Chen Lin
5. Zhenyu Guan
6. Thorsten Holz
7. Xin Deng
8. Paul Bao

Citations in the corpus

• Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding (2018, background): “Watermarking approaches use human perception to hide information about an image, video, or audio clip within itself [5], [14], [57].”
• Protecting Intellectual Property of Deep Neural Networks with Watermarking (2018, methodology): “The most commonly used transforms are the Discrete Cosine Transform (DCT) [25, 44], Discrete Fourier Transform (DFT) [42, 55], Discrete Wavelet Transform (DWT) [9, 11, 31, 58] and the combination of them [6, 38, 46].”
• SVD-based digital image watermarking scheme (2005, background): “Keywords: Image watermarking; Singular value decomposition”
• Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Object Tracking (2018, background): “, image classification [60] and image compression [61].”
• HiNet: Deep Image Hiding by Invertible Network (2021, methodology): “In addition to LSB, there are many methods proposed to embed information in frequency domains, such as discrete Fourier transform (DFT) domain [24], discrete cosine transform (DCT) domain [13], and discrete wavelet transform (DWT) domain [6].”
• Watermarking Deep Neural Networks for Embedded Systems (2018, methodology): “The correlation-based approach has been applied in the spatial domain and in a transform domain such as the wavelet domain [5].”
• Image adaptive watermarking using wavelet domain singular value decomposition (2005, methodology): “[10] proposed a watermarking algorithm based on the”
• A new robust reference watermarking scheme based on DWT-SVD (2009, methodology): “Barni et al. [7] proposed a wavelet domain based method which exploits the characteristics of human visual system (HVS).”