• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.275-286
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• 2010

Reversible watermarking which can preserve the original quality of the digital contents and protect the copyright has been studied actively. Especially, in medical, military, and art fields, the need for reversible watermarking is increasing. This paper proposes a high-capacity reversible watermarking through predicted error expansion and error estimation compensation. Watermark is embedded by expanding the difference histogram between the original value and the predicted value. Differently from previous methods calculating the difference between adjacent pixels, the presented method calculates the difference between the original value and the predicted value, and that increases the number of the histogram value, where the watermark is embedded. As a result, the high capacity is achieved. The inserted watermark is extracted by restoring the histogram between the original value and the predicted value. To prove the performance, the presented algorithm is compared with other previous methods on various test images. The result supports that the presented algorithm has a perfect reversibility, a high image quality, and a high capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.655-670
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• 2010

To be reversible as a data hiding method, the original content and hidden message should be completely recovered. One important objective of this approach is to achieve high embedding capacity and low distortion. Using predicted errors is very effective for increasing the embedding capacity. Sorting the predicted errors has a good influence on decreasing distortion. In this paper, we present an improved reversible data hiding scheme using upgraded histogram shifting based on sorting the predicted errors. This new scheme is characterized by the algorithm which is able to find the optimum threshold values and manage the location map effectively. Experimental results compared with other methods are presented to demonstrate the superiority of the proposed method.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.417-429
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• 2010

Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved and then enables to restore the original media from the marked one without any loss of media quality. This watermarking can be applied to quality-sensitive imaging such as medical imaging, military imaging, remote-sensing imaging, and precious artwork, where the original media should be preserved during image processing and analysis. In this paper, a reversible image watermarking technique that embeds message bits by modifying the differential histogram of adjacent pixels is presented. In order to satisfy both high embedding capacity and visual quality, the proposed technique exploits the fact that adjacent pixels in the image have highly spatial correlation. Also, we prevent overflow/underflow problem and salt-and-pepper artifacts by employing a predicted error compensation scheme. Through experiments using various test images, we prove that the presented technique provides perfect reversibility and high embedding capacity, while maintaining the induced-distortion low.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.231-240
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• 2015

Medical imagery require to protect the privacy with preserving the quality of the original contents. Therefore, reversible watermarking is a solution for this purpose. Previous researches have focused on general imagery and achieved high capacity and high quality. However, they raise a distortion over entire image and hence are not applicable to medical imagery which require to preserve the quality of the objects. In this paper, we propose a novel reversible watermarking for medical imagery, which preserve the quality of the objects and achieves high capacity. First, object and background region is segmented and then predicted error histogram-based reversible watermarking is applied for each region. For the efficient watermark embedding with small distortion in the object region, the embedding level at object region is set as low while the embedding level at background region is set as high. In experiments, the proposed algorithm is compared with the previous predicted error histogram-based algorithm in aspects of embedding capacity and perceptual quality. Results support that the proposed algorithm performs well over the previous algorithm.