Quantization index modulation: a class of provably good methods for digital watermarking and information embedding

By Brian Chen, Gregory W. Wornell. 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060), 2000

2,324 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/91f0624446a323b7642d06ea2a8a6bcda80165f9

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. A. Bovik
2. Zhou Wang
3. Dacheng Tao
4. Luc Van Gool
5. Ming-Hsuan Yang
6. Lei Zhang
7. Radu Timofte
8. Chen Change Loy

In Electrical and Electronic Engineering

1. Uri Erez
2. Ralf Koetter
3. Pierre Moulin
4. Ram Zamir
5. Shlomo Shamai
6. Y. Shi
7. Junhui He
8. Nirwan Ansari

Citations in the corpus

• Quality-aware images (2006, methodology): “This method is a simple case of the class of quantization-indexmodulation information embedding techniques [36], which allow for “blind” decoding (decoding does not require the access to the reference image) and achieve a good tradeoff between data-hiding rate and robustness.”
• Current status and key issues in image steganography: A survey (2014, neutral): “Quantization index modulation (QIM) [37] is one of the promising data embedding technique in digital watermarking and it can also be employed for steganography.”
• Data-Hiding Codes (2005, background): “Chen and Wornell showed how to extend the scalar QIM scheme above to embed one bit in a length- host sequence.”
• Capacity and lattice strategies for canceling known interference (2005, methodology): “…has recently received much attention as it has been demonstrated that it models well various important communication problems, among them precoding for intersymbol interference (ISI) channels [15], [16], [20], digital watermarking (e.g., [13], [4]), and various broadcast schemes (e.g., [3], [40]).”
• Reversible data hiding (2003, methodology): “With the third group of frequently used watermarking techniques, called quantization index modulation (QIM) [ 3 ], quantization error renders lossy data hiding.”
• Detecting Steganographic Content on the Internet (2002, background): “There are three different aspects to an information hiding system that content with one another: capacity, security and robustness [2].”
• Reversible data hiding (2006, background): “Another category of data hiding techniques, quantization-index-modulation (QIM) based schemes (e.g., [8] and [9]), are not distortion-free owing to quantization error.”
• Nested linear/Lattice codes for structured multiterminal binning (2002, background): “The underlying interpretation giving rise to the nested lattice techniques, mentioned also in [9] and [101], conforms, in fact, to the basic insight provided by the Marton approach in deriving achievable rates for general broadcast channels [60] and evidently yields here, in the degraded channel cas”
• ReDMark: Framework for residual diffusion watermarking based on deep networks (2018, methodology): “They use Dither modulation method [41] for embedding in this domain.”
• Watermarking security: theory and practice (2005, background): “Some key events in this quest are the use of spread spectrum [1 ], the invention of resynchronization schemes [2], [3], the discovery of side information channel [4], [5], and the formulation of the opponent actions as a game [6].”
• Anti-collusion fingerprinting for multimedia (2003, background): “1Note that there are other types of watermarking schemes that do not suffer from interference from unknown host signals [12], [21].”