Jingyang Wen

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Reversible data hiding embeds information in a host media in a visually plausible way such that both the embedded message and the original host media can be exactly recovered. In this paper we present a new reversible data hiding framework based on prediction error histogram modification. This framework is general and flexible that includes some of the(More)
Although it has been recognized that different textual contents in an image need to be treated differently during accurate image interpolation, how to classify these contents well has been a difficult problem due to the inherent complexity in natural images. In this paper we propose an efficient image interpolation framework with a novel weighted surface(More)
Image reversible data hiding is the process of embedding information in an image in a visually imperceptible way with the result that both the original image and the embedded information can be exactly recovered. In the traditional approaches of histogram shifting and causal window-based difference/prediction-error expansion, pixel value prediction methods(More)
An adaptive reversible data hiding method through autoregression is presented in this paper. In the proposed algorithm, we focus on the image pixel value prediction, which plays a key role in the data embedding process. Unlike conventional data hiding techniques, a threshold is adjusted for each image to divide all pixels into two regions: the smooth region(More)
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