VQ Image Compression Steganography Based on Section-Based Informed Embedding

In this paper, a steganographic system for VQ codebooks using section-based informed embedding (SBIE) is presented. The goal is to offer a stego-image for secure communication. In the proposed scheme, the secret image is first compressed by a unsupervised fuzzy competitive learning network clustering technology (named FCLN) based on VQ, then a section-based informed embedding algorithms are presented to provide the mechanism of the hiding system for adjustable robustness and fidelity performance. The FCLN generate optimal codebook for VQ. Then we embedded VQ codebook of secret image information into the cover image by a section-based informed embedding scheme. Finally, the experimental results demonstrate two objectives: (1) the promising codebook can be obtained using our proposed image compression scheme FCLN method, and (2) the high fidelity performance offered by the presented SBIE algorithm.