Reversible Data Hiding Considering Shifting Direction and Human Visual Sensitivity

Abstract:

In view of the technique “A New Histogram Modification Based Reversible Data Hiding Algorithm Considering the Human Visual System” by Jung et al., some modifications have been made on the parts of the causal window and the pixel overflow/underflow in present study. In Jung et al.’s method, the number of reference pixel was obtained based on a causal window so that the prediction value, the just noticeable difference (JND) and others can be determined. However, the causal window used in Jung et al.’s method may reduce the prediction accuracy. In this paper, the modifications on two parts are proposed to turn around this situation. First, the causal window is narrowed to decrease the number of reference pixels so that the prediction accuracy can be enhanced. Second, in dealing with possible pixel underflow or overflow, only the pixels that will definitely underflow or overflow, are modified. Using such modifications both the payload and the image quality can be improved. It is shown by experiments that our modifications not only increase payload but also maintain image quality effectively.

• Periodical: Advanced Engineering Forum (Volumes 6-7)
• Pages: 422-427
• DOI: https://doi.org/10.4028/www.scientific.net/AEF.6-7.422
• Online since: September 2012
• Authors: Han Yan Wu, Yan Wei Li, Jean Ne Chen, Wien Hong
• Keywords: Embedding Level, Just Noticeable Difference, Location Map

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