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Proceedings ArticleDOI

Reversible Image Watermarking Using a Diagonal Structure for Prediction

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TLDR
Experiments show that the proposed schemes generally outperform some existing schemes in terms of embedding rate versus distortion, and the host image can be blindly recovered with the overhead information hidden in it.
Abstract
This paper presents a study on the prediction-based reversible data hiding for digital images. By adopting a diagonal structure for prediction, a large number of pixels in the host image can be predicted and further modified for data embedding. Two prediction schemes are derived from the same structure so that the performance with the different numbers of prediction errors can be compared. For either scheme, the optimal prediction mode is found out to minimize the distortion of the host after embedding a certain amount of information. Besides, the host image can be blindly recovered with the overhead information hidden in it. Experiments show that the proposed schemes generally outperform some existing schemes in terms of embedding rate versus distortion.

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References
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Journal ArticleDOI

Reversible data embedding using a difference expansion

TL;DR: The redundancy in digital images is explored to achieve very high embedding capacity, and keep the distortion low, in a novel reversible data-embedding method for digital images.
Journal ArticleDOI

Reversible data hiding

TL;DR: It is proved analytically and shown experimentally that the peak signal-to-noise ratio of the marked image generated by this method versus the original image is guaranteed to be above 48 dB, which is much higher than that of all reversible data hiding techniques reported in the literature.
Journal ArticleDOI

Expansion Embedding Techniques for Reversible Watermarking

TL;DR: The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion, and there is a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities.
Journal ArticleDOI

Reversible Watermarking Algorithm Using Sorting and Prediction

TL;DR: This paper presents a reversible or lossless watermarking algorithm for images without using a location map in most cases that employs prediction errors to embed data into an image.
Book ChapterDOI

Reversible data hiding

TL;DR: A theoretical proof and numerous experiments show that the PSNR of the marked image generated by this method is always above 48 dB, which is much higher than other reversible data hiding algorithms.
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