A semi-fragile reversible watermarking method based on qdft and tamper ranking

被引:3
作者
Ouyang, Junlin [1 ,2 ,3 ]
Huang, Jingtao [1 ,2 ]
Wen, Xingzi [2 ]
机构
[1] Hunan Univ Sci & Technol, Sch Comp Sci & Engn, Xiangtan 411201, Peoples R China
[2] Hunan Key Lab Serv Comp & Novel Software Technol, Xiangtan 411201, Peoples R China
[3] Hunan Software Vocat & Tech Univ, Xiangtan 411100, Peoples R China
关键词
Semi-fragile reversible watermarking; Quaternion discrete Fourier transform; Tamper localization; Image forensics; IMAGE AUTHENTICATION; INTEGER TRANSFORM; DIFFERENCE;
D O I
10.1007/s11042-023-16963-w
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The traditional semi-fragile watermarking can effectively protect the integrity of the host image, but the permanent distortion caused by watermark embedding makes the application in high-fidelity images limited. Hence, we propose a novel semi-fragile reversible watermarking scheme for tampering localization. The motivation of this research is to solve the problem that the original carrier cannot be recovered in semi-fragile watermarking method and to improve the accuracy of tampered image detection and location. The proposed scheme embeds the semi-fragile watermark into the mid-frequency quaternion discrete Fourier transform (QDFT) coefficients to provide semi-fragility and reversibly embeds the compensation information into the watermarked image to achieve cover-lossless. First, to reduce the amount of compensation information, the watermarked image is pre-recovered using the neighborhood coefficients of the semi-fragile watermark embedding position. Then, the difference between the pre-recovered image and the original image is represented by the frequency domain error and the spatial domain error. Secondly, the performance of tampering localization is improved by optimizing the graph structure and weight matrix in the manifold ranking (MR) model. Specifically, a new approximate k-regular graph is constituted by introducing spatial relations of neighbors, that must be linked and must not be linked, which are integrated into the original graph structure. Then, a new weight matrix is constructed by combining multi-view features, to enhance the shape performance of the localized regions. The experimental results show that the proposed method can effectively resist content retention attacks, and accurately locate tampered regions. In the event of a non-attack, the original image can be recovered losslessly.
引用
收藏
页码:41555 / 41578
页数:24
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