| Summary: | As an effective means to content authentication and privacy protection, reversible data hiding (RDH) permits us to hide a payload such as authentication data in a media file. The resulting marked content will not introduce noticeable artifacts. In order to achieve superior payload-distortion performance, the conventional RDH algorithms often exploit the smooth content for data embedding. Since RDH allows both the embedded payload and the raw content to be perfectly reconstructed, it is required that, the altered smooth regions within the cover should be identified without error by a data receiver. Therefore, a core work in RDH is to design an efficient content-aware algorithm that can enable a data hider to take advantages of the smooth cover elements as much as possible while the detection procedure for the marked elements should be invertible to a data receiver. This has motivated the authors to present a novel patch-level selection and breadth-first prediction strategy for efficient RDH in this paper. However, different from many conventional RDH works, the proposed approach allows a data hider to preferentially and simultaneously use adjacent smooth elements as many as possible, which can benefit data embedding procedure a lot. Experiments show that our work significantly outperforms a part of advanced RDH algorithms in terms of the payload-distortion performance, which has demonstrated the superiority and applicability.
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