Information Hiding Based on Block Match Coding for Vector Quantization-Compressed Images
In this paper, a novel highly efficient lossless data hiding scheme is proposed to achieve the goal of hiding secret data into vector quantization (VQ)-compressed images that can be losslessly reconstructed after the secret data is extracted in the decoder. For VQ-compressed images, the index-modifying and the side-match VQ (SMVQ) techniques can be applied to encode indices and hide secret data. In general, data hiding accompanied by the SMVQ technique can yield a higher embedding capacity and a lower bit rate, yet more time consuming. In contrast, data hiding accompanied by the index-modifying technique can yield a lower embedding capacity and a higher bit rate, yet less time consuming. To possess the advantages of the two techniques while removing the shortcomings, the neighboring processed indices are employed to speed up the processes of generating state codebooks required for encoding and hiding. To evaluate the effectiveness of this approach, various test images are employed in the experiments. As documented in the experimental results, it is shown that the performance of the proposed scheme is superior to former schemes in terms of compression ratio, embedding rate, processing efficiency, and embedding capacity.