Reversible data hiding based on search-order coding for VQ-compressed images

Vector Quantization (VQ) is a popular digital image compression technique. Since VQ significantly reduces the size of a digital image, the technique which can save the costs of storage space and image delivery. This scheme uses Search-Order Coding (SOC) to manipulate the rather random distributed histogram of a VQ-compressed image into locations close to zero, then uses encoding strategies to perform encoding and data hiding simultaneously. In encoding process, no indicator is required for indices to identify index types, which helps improve compression performance. Furthermore, the proposed scheme can completely restore the VQ-compressed image after secret data extraction. Experimental results demonstrate that the proposed scheme significantly enhances the compression ratio and embedding capacity. Experimental results also show that the proposed scheme achieves the best performance among approaches in literature in terms of the embedding rate, the bit rate, and the embedding capacity.