Multi-Carrier Information Hiding Algorithm Based on GHM Multiwavelet Transform and Singular Value Decomposition

Abstract

Aiming at the problem that the single-carrier information hiding algorithm is limited by the number of carriers, and its capacity and security cannot be further broken through, a digital image multi-carrier information hiding algorithm based on Geronimo Hardin Massopus (GHM) and singular value decomposition (SVD) is proposed. Firstly, the digital image is classified based on the color histogram and LDP fusion characteristics of the digital image. Secondly, the GHM multiwavelet transform is applied and the information hiding area is selected according to the energy characteristics. Finally, while ensuring the correlation between images, the carrier image is slightly modified in combination with the stability of singular value to embed secret information. By applying GHM multiwavelet transform to the carrier image, the data is embedded in the subgraph with relatively low energy weight, which effectively improves the concealment and anti-analysis of the algorithm. Using the unique stability and rotation invariance of image singular value, it is slightly modified to embed secret information in the carrier image, reduce the embedding distortion and improve the robustness of the proposed algorithm. Experimental analysis shows that compared with the comparison algorithm, the advantage of the algorithm is that the invisibility PSNR value is increased by 27.05% and 9.46% on average. When facing the high-intensity composite attack of 30% shear, JPEG2000 compression and 33° counterclockwise rotation at the same time, the PSNR can reach 39.3274dB, and its invisibility and robustness have been significantly improved.