An adaptive high capacity reversible data hiding algorithm in interpolation domain

• Published in: Signal processing Vol. 194; p. 108458
• Main Authors: Xiong, Xiangguang, Wang, Lihui, Li, Zhi, Ye, Chen, Chen, Yi, Fan, Mengting, Zhu, Yuemin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2022; Elsevier
• Subjects: Adaptive embedding; Computer Science; Location-dependent weighted image interpolation; Medical Imaging; Reversible data hiding; Steganalysis; Adaptive embedding; Reversible data hiding; Steganalysis; Location-dependent weighted image interpolation
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2022.108458

•Propose an adaptive weighted-based image interpolation algorithm.•To guarantee the visual quality of watermarked image, a threshold T is used to determine whether the difference can be embedded in secret data.•Embed data in the blocks with small deviation with priority for improving further the image quality at low embedding rates.•To overcome the overflow or underflow problem, we present two temporary embedded pixels to help us choose adaptively the final embedded result. [Display omitted] Reversible data hiding (RDH) algorithms using interpolation technology have the advantage of high capacity for single-layer embedding. However, existing algorithms usually embed secret data in the non-reference pixels based on simple additions without considering the properties of context-pixels, which results in that the visual quality of watermarked image is not optimal. To deal with this issue, a novel adaptive high capacity RDH algorithm is proposed. Firstly, a location-dependent weighted image interpolation method is proposed to improve the visual quality of the interpolated image. Then, the interpolated image is divided into overlapping blocks, which are sorted in an ascending order according to their standard deviations; secret data is preferentially embedded in the blocks with small deviation so that image quality is not distorted too much. Finally, to enhance embedding capacity as much as possible, the amount of secret data bits that can be embedded in non-reference pixels is calculated adaptively. We theoretically prove that the embedded secret data can be extracted correctly and there is no pixel overflow or underflow problem. Extensive experimental results showed that the proposed algorithm outperforms several state-of-the-art algorithms. In addition, our algorithm can resist steganalysis attacks, and demonstrated the effectiveness of the proposed algorithm.