An adaptive high capacity reversible data hiding algorithm in interpolation domain

被引:16
作者
Xiong, Xiangguang [1 ,3 ]
Wang, Lihui [1 ]
Li, Zhi [1 ]
Ye, Chen [1 ]
Chen, Yi [3 ]
Fan, Mengting [3 ]
Zhu, Yuemin [2 ]
机构
[1] Guizhou Univ, Coll Comp Sci & Technol, Key Lab Intelligent Med Image Anal & Precise Diag, Guiyang 550025, Peoples R China
[2] Univ Lyon, INSA Lyon, Inserm U1206, CNRS,UMR5220, F-69621 Lyon, France
[3] Guizhou Normal Univ, Sch Big Data & Comp Sci, Guiyang 550025, Peoples R China
基金
中国国家自然科学基金;
关键词
Reversible data hiding; Location-dependent weighted image; interpolation; Adaptive embedding; Steganalysis; DIFFERENCE EXPANSION; HISTOGRAM; SCHEME;
D O I
10.1016/j.sigpro.2022.108458
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A B S T R A C T 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.(c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:16
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