Reversible data hiding of a VQ index table based on referred counts
This paper presents a new reversible VQ-based hiding scheme that can recover the original VQ compressed codes after data extraction. Our scheme sorts a VQ codebook using the referred counts. The VQ codebook is then divided into 2B clusters and half of these clusters are used to embed secret data, in which B denotes the size of the secret data embedded into each VQ index. Compared to Chang et al.s scheme, which divides a sorted VQ codebook into 2B?13 clusters and uses the front one-third clusters to embed secret data, our method can embed more data. Moreover, indicator, index exchanging, and side-match prediction schemes are proposed to further improve our scheme. Under the same sorted VQ codebook, the experimental results demonstrate that our data hiding algorithm has higher capacities and better compression rates.
data hiding side-match reversible embedding vector quantization codebook clustering lossless compression steganography predictive coding