An efficient histogram-based index mapping mechanism for reversible data hiding in VQ-compressed images.

In this paper, a reversible data hiding scheme for vector quantization (VQ)-compressed images is proposed. The scheme introduces two methods to explore the high correlations between VQ indices of an index table, followed by exploiting the redundancy elimination for data embedding. The first method utilizes the concept of side matching and the second one uses the feature of locally repetitive occurrence of the VQ indices in VQ-compressed images. In this research, some concepts of information theory are studied to design an efficient index mapping mechanism in the embedding capacity point of view. The proposed index mapping mechanism partitions the positions of the sorted codebook into some intervals, and assigns each interval of the positions to each position with high hit rate in the sorted codebook. Then, based on the secret bits, each index located in the positions of the sorted codebook with high hit rates is mapped to one of the indices in the interval assigned to that position. Furthermore, an interval of the sorted codebook is reserved as the indicator of the indices with low hit rates. The experimental results demonstrate that the proposed scheme significantly outperforms the existing schemes in terms of the embedding capacity and compression-embedding efficiency.