Histogram-based reversible data hiding technique using subsampling
Proceedings of the 10th ACM workshop on Multimedia and security
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IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
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IEICE - Transactions on Information and Systems
Reversibility improved lossless data hiding
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IEEE Transactions on Image Processing
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IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
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IEEE Transactions on Circuits and Systems for Video Technology
Information Sciences: an International Journal
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Multimedia Tools and Applications
Reversibility of image with balanced fidelity and capacity upon pixels differencing expansion
The Journal of Supercomputing
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This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.