A steganographic method for images by pixel-value differencing
Pattern Recognition Letters
Reversible data hiding for high quality images using modification of prediction errors
Journal of Systems and Software
Reversible data hiding based on histogram modification of pixel differences
IEEE Transactions on Circuits and Systems for Video Technology
DE-based reversible data hiding with improved overflow location map
IEEE Transactions on Circuits and Systems for Video Technology
A High Capacity Reversible Watermarking Scheme Based on an Integer Transform
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Reversible image watermarking using interpolation technique
IEEE Transactions on Information Forensics and Security
YASS: yet another steganographic scheme that resists blind steganalysis
IH'07 Proceedings of the 9th international conference on Information hiding
IEEE Transactions on Signal Processing - Part II
Adaptive Data Hiding in Edge Areas of Images With Spatial LSB Domain Systems
IEEE Transactions on Information Forensics and Security
Reversible watermark using the difference expansion of a generalized integer transform
IEEE Transactions on Image Processing
Expansion Embedding Techniques for Reversible Watermarking
IEEE Transactions on Image Processing
Reversible data embedding using a difference expansion
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Journal of Systems and Software
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In this paper, we present a new reversible data hiding algorithm based on integer transform and adaptive embedding. According to the image block type determined by the pre-estimated distortion, the parameter in integer transform is adaptively selected in different blocks. This allows embedding more data bits into smooth blocks while avoiding large distortion generated by noisy ones, and thus enables very high capacity with good image quality. For instance, by the proposed method, we can embed as high as 2.17bits per pixel into Lena image with a reasonable PSNR of 20.71dB. Experimental results demonstrate that the proposed method outperforms some state-of-the-art algorithms, especially for high capacity case.