An Efficient Reversible Data Hiding Scheme Based on Reference Pixel and Block Selection

To combine homomorphic public key encryption with reversible data hiding, a reversible data hiding scheme in homomorphic encrypted image based on EC-EG is proposed. Firstly, the cover image is segmented. The square grid pixel group randomly selected by the image owner has one reference pixel and eight target pixels. The n least significant bits (LSBs) of the reference pixel and all bits of target pixel are self-embedded into other parts of the image by a method of predictive error expansion (PEE). To avoid overflowing when embedding data, the n LSBs of the reference pixel are reset to zero before encryption. Then, the pixel values of the image are encrypted after being encoded onto the points of the elliptic curve. The encrypted reference pixel replaces the encrypted target pixels surrounding it, thereby constructing the mirroring central ciphertext (MCC). In a set of MCC, the data hider embeds the encrypted additional data into the n LSBs of the target pixels by homomorphic addition in ciphertexts, while the reference pixel remains unchanged. The receiver can directly extract additional data by homomorphic subtraction in ciphertexts between the target pixels and the corresponding reference pixel; extract the additional data by subtraction in plaintexts with the directly decrypted image; and restore the cover image without loss. The experimental results show that the proposed scheme has higher security than the similar algorithms, and the average embedding rate of the scheme is 0.25 bpp under the premise of ensuring the quality of the directly decrypted image.

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Reversible Data Hiding Considering Shifting Direction and Human Visual Sensitivity

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.6-7.422 ◽

2012 ◽

Vol 6-7 ◽

pp. 422-427

Author(s):

Han Yan Wu ◽

Yan Wei Li ◽

Jean Ne Chen ◽

Wien Hong

Keyword(s):

Image Quality ◽

Visual System ◽

Data Hiding ◽

Human Visual System ◽

Reversible Data Hiding ◽

Prediction Accuracy ◽

Visual Sensitivity ◽

Just Noticeable Difference ◽

Histogram Modification ◽

Reference Pixel

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.

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