Abstract
In reversible data embedding, to avoid overflow and underflow problem, before data embedding, boundary pixels are recorded as side information, which may be losslessly compressed. The existing algorithms often assume that a natural image has few boundary pixels so that the size of side information could be rather small. Accordingly, a relatively high pure payload could be achieved. However, there actually may exist a lot of boundary pixels in a natural image, implying that, the size of side information could be very large. Thus, when to directly use the existing algorithms, the pure embedding capacity may be not sufficient. In order to address this important problem, in this paper, we present a new and efficient framework to reversible data embedding in images that have lots of boundary pixels. The core idea is to losslessly preprocess boundary pixels so that it can significantly reduce the side information. We conduct extensive experiments to show the superiority and applicability of our work.
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Notes
- 1.
Online available: http://agents.fel.cvut.cz/stegodata/.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China under Grant Nos. 61502496, U1536120, and U1636201, and the National Key Research and Development Program of China under Grant No. 2016YFB1001003, Key Lab of Information Network Security, Ministry of Public Security.
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Wu, H., Wang, W., Dong, J., Chen, Y., Wang, H., Wu, S. (2018). Reversible Embedding to Covers Full of Boundaries. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11066. Springer, Cham. https://doi.org/10.1007/978-3-030-00015-8_35
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