Abstract: Adaptive most significant bit prediction (AMP) is an important technique to achieve reversible data hiding in encrypted images. AMP typically predicts pixel values by comparing the first pixel within a block with the remaining ones, extracting the longest common most significant bits to create space for embedding secret information. However, the significant difference between the first pixel and others can limit the embedding capacity. To solve this problem, this paper aggregates the unchanged pixels after data embedding within blocks and constructs a virtual pixel block. By applying the AMP algorithm again to the virtual pixel block, the proposed scheme enhances the embedding capacity. In order to further increase the number of virtual pixel blocks, this paper proposes a filling strategy. Taking a 2×2 pixel block as an example, when the block’s embedding capacity is large enough, the pixel correlation is increased by filling fixed bits. This ensures the first two pixels remain unchanged during embedding and can all be used to construct a virtual block. Because of the T field constructed by the filling strategy and the new 32 bits pixel structure proposed, pixel correlation is enhanced and embedding capacity is increased as a result. Experimental results on real-world datasets demonstrate that the proposed algorithm significantly outperforms existing AMP algorithms in terms of embedding capacity while maintaining data reversibility.

Key words: image encryption, multimedia security, reversible data hiding, adaptive most significant bit prediction