Local-Prediction-Based Difference Expansion Reversible Watermarking

This paper investigates the use of local prediction in difference expansion reversible watermarking. For each pixel, a least square predictor is computed on a square block centered on the pixel and the corresponding prediction error is expanded. The same predictor is recovered at detection without a...

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Bibliographic Details
Published inIEEE transactions on image processing Vol. 23; no. 4; pp. 1779 - 1790
Main Authors Dragoi, Ioan-Catalin, Coltuc, Dinu
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.04.2014
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
adaptive prediction
Applied sciences
Blocking
Computation
Context
Cryptography
difference expansion
Equations
Exact sciences and technology
Histograms
Image coding
Image edge detection
Image processing
Information, signal and communications theory
least square predictors
Least squares method
Pattern recognition
Pixels
Reversible watermarking
Signal and communications theory
Signal processing
State of the art
Telecommunications and information theory
Transaction processing
Vectors
Watermarking
Performance evaluation
State of the art
least square predictors
Predictor
Reversible watermarking
Pattern recognition
Shape detection
Least squares method
Information protection
Edge detection
Digital watermarking
adaptive prediction
difference expansion
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Summary:This paper investigates the use of local prediction in difference expansion reversible watermarking. For each pixel, a least square predictor is computed on a square block centered on the pixel and the corresponding prediction error is expanded. The same predictor is recovered at detection without any additional information. The proposed local prediction is general and it applies regardless of the predictor order or the prediction context. For the particular cases of least square predictors with the same context as the median edge detector, gradient-adjusted predictor or the simple rhombus neighborhood, the local prediction-based reversible watermarking clearly outperforms the state-of-the-art schemes based on the classical counterparts. Experimental results are provided.
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ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2014.2307482