Abstract
Hiding data on grayscale images has been drawing much attention in recent years. High capacity and better image quality are the two foremost research contents of data hiding. The traditional EMD which concealed an equal amount of data into each pixel and cause equal degree of distortion. Meanwhile due to being only an approximation, an interpolated image will always lose some quality each time interpolation is performed. In view of the problems existing in the two above method, we propose a novel data hiding scheme that employs human vision sensitivity to hide a large amount of secret bits into a original image with a high imperceptibility and low computational complexity. Experimental results reveal that the proposed method performs better than several state-of-the-art methods. It can resist the RS steganalysis attack and it is statistically invisible for the attack of PVD histogram attack.
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Acknowledgements
This work was supported by the Natural Science Foundation of P.R. China (11371127,11571124, 61572028), the Guangdong Applied Science and Technology Research Foundation of P.R. China (2016B020244003), the major Guangzhou University-industry Collaboration Innovation Project (201604016002,201704020203), and Young Teachers Scientific Research and Cultivating Foundation of South China Normal University (15KJ06).
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Shen, Sy., Huang, Lh. & Yu, Ss. A novel adaptive data hiding based on improved EMD and interpolation. Multimed Tools Appl 77, 12563–12579 (2018). https://doi.org/10.1007/s11042-017-4905-5
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DOI: https://doi.org/10.1007/s11042-017-4905-5