Aiming at the security problem of secret information preprocessing and the difficulty of improving the capacity and robustness of the single-carrier image information hiding algorithm, an identifiable tampering multi-carrier image information hiding algorithm based on compressed sensing is proposed. Firstly, the angle structure descriptor feature vector was used to preprocess and classify the image carrier set. Secondly, the GHM multiwavelet transform was applied to different types of image carriers to obtain the secret information hiding area which can balance the invisibility and robustness. Thirdly, the secret image was processed by compressed sensing, the resulting observation matrix was decomposed by singular value, and the chaotic scrambling was encoded by logistic mapping. Finally, the secret information was embedded in the image singular value to complete the information hiding of different types of multiquantity image carriers. Combined with the angle structure descriptor of the image, the algorithm proposed an effective way to organize multiple carriers, which improved the embedding quality and efficiency of secret information. The verification data and segmented secret information classification and embedding strategy made the proposed algorithm have a keen ability to detect tampering and effectively improve the efficiency and integrity of secret information extraction. Experimental results show that compared with image sharing information hiding algorithm and the single-carrier information hiding algorithm based on compressed sensing, the invisibility and robustness of our algorithm are significantly improved. At the same time, the proposed algorithm has strong anti-analysis ability, can effectively resist most image processing attacks, and is suitable for large capacity secret communication and high-security applications. INDEX TERMS Multi-carrier information hiding, compressed sensing, angle structure descriptor, multiwavelet transform, singular value decomposition.

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