The proliferation of digital information in our society has enticed a lot of research into data embedding techniques that add information to digital content like images, audio and video. This additional information can be used for various purposes and different applications place different requirements on the embedding techniques. In this paper, we investigate high capacity lossless data embedding methods that allow one to embed large amounts of data into digital images (or video) in such a way that the original image can be reconstructed from the watermarked image. The paper starts by briefly reviewing three existing lossless data embedding techniques as described by Fridrich and co-authors, by Tian, and by Celik and co-workers. We then present two new techniques: one based on least significant bit prediction and Sweldens' lifting scheme and another that is an improvement of Tian's technique of difference expansion. The various embedding methods are then compared in terms of capacity-distortion behaviour, embedding speed, and capacity control.

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CWI. Probability, Networks and Algorithms [PNA]
Signals and Images

Kamstra, L., & Heijmans, H. (2004). Wavelet techniques for reversible data embedding into images. CWI. Probability, Networks and Algorithms [PNA]. CWI.