Expansion Embedding Techniques for Reversible Watermarking

By Diljith M. Thodi, Jeffrey J. Rodríguez. IEEE Transactions on Image Processing, 2007

1,523 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/5dc7550421c29844047b58a126fdf54164677e0a

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In Computer Vision and Pattern Recognition

1. Xiaolong Li
2. Bin Yang
3. Weiming Zhang
4. Dinu Coltuc
5. Xinpeng Zhang
6. Nenghai Yu
7. Xinlu Gui
8. Kede Ma

Citations in the corpus

• An Improved Reversible Data Hiding in Encrypted Images Using Side Match (2012, methodology): “[4] adopts the difference expansion and histogram shifting for data embedment.”
• Reversibility improved data hiding in encrypted images (2014, methodology): “After generating the estimating errors, difference expanding method in [4] or histogram shifting method in [7] can be applied to these errors to embed the location maps O 1 and O 2 .”
• Pairwise Prediction-Error Expansion for Efficient Reversible Data Hiding (2013, methodology): “, 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.”
• Efficient Reversible Data Hiding Based on Multiple Histograms Modification (2015, methodology): “Afterwards, the expansion technique has been widely investigated and developed, mainly in the aspects of integer-to-integer transformation [18]–[22], location map reduction [23]–[25], and prediction-error expansion (PEE) [26]–[35].”
• DE-Based Reversible Data Hiding With Improved Overflow Location Map (2009, methodology): “A predictor [ 21 ] below can exploit the neighboring information to predict an image pixel”
• Local-Prediction-Based Difference Expansion Reversible Watermarking (2014, methodology): “obtained by embedding into each pixel (see [11]).”
• Reversible Data Hiding in Encrypted Images by Reserving Room Before Encryption (2013, methodology): “The state-of-art methods [7]–[11] usually combined DE or HS to residuals of the image, e.g., the predicted errors, to achieve better performance.”
• Improved Embedding for Prediction-Based Reversible Watermarking (2011, methodology): “In [16] and [17], as in many other schemes, the MED predictor is used.”
• Efficient Reversible Watermarking Based on Adaptive Prediction-Error Expansion and Pixel Selection (2011, methodology): “For example, the context adaptive predictor median edge detector (MED [26]) is employed in many works [13]–[15]: if , if , otherwise, where , and are the right, lower and diagonal neighbors of (see Fig.”
• A Novel Difference Expansion Transform for Reversible Data Embedding (2008, methodology): “The data-hiding method of Thodi and Rodriguez [13] can be a good reference for the reduced size of a location map.”
• A Novel Reversible Data Hiding Scheme Based on Two-Dimensional Difference-Histogram Modification (2013, methodology): “This method performs well and it is superior to some typical RDH schemes such as [6], [14] and [20].”
• Reversible data hiding for high quality images using modification of prediction errors (2009, methodology): “These methods exploit either expansion embedding technique (Tian, 2003; Kamstra and Heijmans, 2005; Thodi and Rodriguez, 2007), or histogram-shifting technique (Xuan et al., 2007) to achieve an acceptable image quality.”
• Reversible data hiding: Advances in the past two decades (2016, methodology): “2, we emphasize that PEE [36] can be and have been widely utilized by HS for performance enhancement as well.”
• General Framework to Histogram-Shifting-Based Reversible Data Hiding (2013, methodology): “2246179 difference expansion (DE) [8]–[10], histogram shifting (HS) [11]–[13], and integer transform [14]–[17], etc.”
• Reversible Data Hiding Based on Histogram Modification of Pixel Differences (2009, methodology): “Tian’s technique has been extended recently in [9]–[11].”
• Multilevel reversible data hiding based on histogram modification of difference images (2008, methodology): “[15] used a histogram shifting technique to embed the location map for solving the location map problem generated by DE, and also proposed a prediction-error expansion approach that better exploited the correlation inherent in the neighborhood of a pixel than the DE scheme.”
• Reversible Watermarking Algorithm Using Sorting and Prediction (2009, methodology): “The histogram shift scheme of Thodi and Rodriguez [13] is utilized in this paper to enhance performance.”