Lossless watermarking for image authentication: a new framework and an implementation

By Mehmet Utku Celik, Gaurav Sharma, A. Tekalp. IEEE Transactions on Image Processing, 2006

314 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/fbe45a857f20a6b518fcc2eece00e8acfbe7642a

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. Xiaolong Li
2. Weiming Zhang
3. Bin Yang
4. Hao-Tian Wu
5. Bin Ma
6. Y. Shi
7. Xinpeng Zhang
8. Wei-Liang Tai

Citations in the corpus

• Reversible data hiding: Advances in the past two decades (2016, background): “Some other initial RDH schemes, either for fragile authentication or high capacity, are based on lossless compression [16]–[24].”
• Efficient Reversible Watermarking Based on Adaptive Prediction-Error Expansion and Pixel Selection (2011, background): “…remote sensing, military image processing, medical image sharing, multimedia archive management, etc. Early reversible watermarking algorithms are mainly based on lossless compression [4]–[8], in which certain features of host image are losslessly compressed to save space for embedding the payload.”
• Pairwise Prediction-Error Expansion for Efficient Reversible Data Hiding (2013, background): “, compression based algorithms [7]–[11], difference expansion (DE) based algorithms [12]–[16], histogram shifting (HS) based algorithms [17]–[19], prediction-error expansion (PEE) based algorithms [20]–[34] and integer-to-integer transform based algorithms [35]–[41], etc.”
• Multilevel reversible data hiding based on histogram modification of difference images (2008, background): “Related applications include embedding private information of patients into the corresponding medical images and providing lossless authentication watermarking for satellite images [8].”
• Efficient Reversible Data Hiding Based on Multiple Histograms Modification (2015, methodology): “Early RDH methods are mainly based on lossless compression [11]–[14].”
• Reversible Data Hiding Based on Histogram Modification of Pixel Differences (2009, methodology): “[6], [7] uses a variant of an arithmetic compression algorithm to encode a message and hide the resulting interval number in the host image.”