Lossless data embedding for all image formats

By Jessica J. Fridrich, Miroslav Goljan, Rui Du. IS&T/SPIE Electronic Imaging, 2002

452 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/9f3c5e84c944c5d7546cb45ddd8f2ce015393af7

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. Weiming Zhang
2. Y. Shi
3. Xiaolong Li
4. Xinpeng Zhang
5. Nenghai Yu
6. Kede Ma
7. Zhenxing Qian
8. Wei-Liang Tai

Citations in the corpus

• Reversible data hiding: Advances in the past two decades (2016, unknown): “In [109], Fridrich et al.”
• Reversible Data Hiding Based on Histogram Modification of Pixel Differences (2009, methodology): “[3], [4] devised an invertible watermarking method by using a lossless compression algorithm to make space in which to embed data.”
• Reversible Data Hiding in Encrypted Images With Distributed Source Encoding (2016, methodology): “Many RDH methods for plaintext images have been proposed [15]–[19], for example, a common framework of redundancy compression [14], difference expansion [15],”
• Reversible Data Hiding in Encrypted Images by Reserving Room Before Encryption (2013, background): “Fridrich et al. [4] constructed a general framework for RDH.”
• Reversible Watermarking Algorithm Using Sorting and Prediction (2009, methodology): “The proposed technique outperforms existing methods such as [1], [5], [17], and [21] by exploiting high-frequency subbands and efficient data hiding technique.”
• Expansion Embedding Techniques for Reversible Watermarking (2007, background): “The other category of approaches [4], [8], [9], [11], [15], sometimes referred to as type-II algorithms in the literature, involves methods to losslessly compress a set of selected features from an image and embed the payload in the space saved due to the compression.”
• Reversibility improved data hiding in encrypted images (2014, methodology): “The values belonging to [1, 7] are shifted toward the right and the values belonging to ½(cid:5) 2 ; (cid:5) 7 (cid:4) are shifted toward the left, which results in the shifted histogram (Fig.”