High capacity SMVQ-based hiding scheme using adaptive index

This paper proposes a high-capacity image-hiding scheme based on an adaptive index. Data-hiding based on vector quantization (VQ) is a technique for hiding data in the VQ index code. Data-hiding based on side match vector quantization (SMVQ) has been proposed for improving the compression rate of VQ-based data-hiding schemes. However, the hiding capacity of an SMVQ-based data-hiding scheme is very low since, at most, only one secret bit is hidden in one index code. To overcome this drawback and increase the capacity, the proposed method uses an adaptive index to hide more bits in one index code. The weighted squared Euclidean distance (WSED) can also be used to increase the probability of SMVQ to get greater hiding capacity. According to the experimental results, a higher hiding capacity was obtained and a good-quality embedded image was preserved in the adaptive index SMVQ-based data-hiding scheme. The hiding capacity of the proposed scheme was approximately twice that of relevant two hiding schemes.