Secure Image Communication Through Adaptive Deer Hunting Optimization Based Vector Quantization Coding of Perceptually Encrypted Images

Communication fields are growing rapidly in the recent era, so transmitting the multimedia contents through an open channel becomes a challenging task. The multimedia contents that are transmitted through this channel are highly prone to vulnerabilities and attacks. Therefore, secure and efficient data communication is considered as a major concern in the multimedia communication systems. So, major efforts are taken by researchers to safeguard the originality of each image. In a conventional system, the secure image communication process was achieved by compressing the content first, and then encryption is performed over the compressed data. Even though it met the required security and compression ratio, but some applications may require the reverse system. In this method, the encryption process is conducted prior to compression to improve the privacy of user data. Moreover, the initial concentration is given for improving content privacy rather than concentrating on size reduction. This paper proposes a reversed system that uses block based perceptual encryption algorithm for encryption and vector quantization (VQ) with hybrid Lloyd–Buzo–Gray (LBG)-Adaptive Deer Hunting Optimization (ADHO) algorithm (VQ-LBG-ADHO) for compression. So, the content secrecy gets improved. The involvement of this adaptive optimization method enhances the performance of VQ in the compression process. This method highly concentrates on secure communication, so the reverse process is followed in this method. It not only improves the image secrecy, however, it further enhances the image quality. The performance of this secure communication process is compared with state-of-the-art algorithms, and the results reveal that the proposed method outperforms the other existing methods.