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1

Reversible Data Hiding Based on Three-Circular-Pixel Difference Expansion

Lin C-C., Yang S-P., Hsueh N-L.

Fundamenta Informaticae

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2009

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Vol. 91, nr 3-4

581-595

EN

This paper proposes a reversible data hiding scheme based on three-circular-pixel (TCP) difference expansion. To embed a message in an image, the image is divided into three-pixel blocks, each of which is, then, transformed into a TCP block with two differences. When the pixel value of the largest pixel in the TCP block is increased, two differences are increased—one is between the largest and the smallest, and the other is between the largest and the middle. Expanding the two differences in the block by increasing the largest pixel value may make the image less modified. In addition, the number of pixel pairs is increased to two thirds of the number of pixels in the image. Compared to Tian's study, both the visual quality and the embedding capacity of the image are significantly improved.

2

High-Performance Reversible Data Hiding

Lin C-C., Hsueh N-L., Shen W-H.

Fundamenta Informaticae

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2008

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Vol. 82, nr 1-2

155-169

EN

This paper proposes a high-performance reversible data hiding algorithm based on the block difference histogram of a cover image. If a message is to be embedded into an image, the difference of the block at the maximum point is increased by 1 or left unchanged if the message bit is 1" or 0", respectively. Experimental results show that the average payload capacity of the test images can be up to 1.52 bits per pixel (bpp). Average payload and pure payload capacities for PSNR ^(3) 30 dB can be up to 1.13 bpp and 1.06 bpp, respectively. Moreover, the original cover image can be recovered without any distortion and the implementation of the proposed algorithm is very easy.

3

Adaptively Embedding Binary Data in an Image

Lin C-C., Hsueh N-L., Shen W-H.

Fundamenta Informaticae

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2008

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Vol. 84, nr 3-4

391-402

EN

In this paper, we propose an embedding algorithm, of high visual quality, that can adaptively embed a binary message into an image. The binary message to be embedded is divided into two segments, each of which is then decomposed into n+1 or n types of sub-messages (where n ^(3) 3 enables each pixel to embed a sub-message), respectively, according to the desired embedding capacity. Embedding is done by leaving the pixel value unchanged or changing it into one of its n or n-1 neighboring values according to the type of the sub-message. From the results of this study, each pixel may not embed a fixed number of message bits and the adjustment of the pixel value is minimal, thus the image quality is significantly improved by adaptively decomposing the message into sub-messages and embedding them into the host image.