Bat optimized 3D anaglyph image watermarking based on maximum noise fraction in the digital Shearlet domain

Abstract

The unparalleled growth of multimedia data sharing through the internet has made copyright protection and authentication a topical affair. In this paper, we propose a robust watermarking scheme for 3D red-cyan anaglyph stereo image authentication and copyright protection with Maximum Noise Fraction in the digital Shearlet domain. A precise Human Visual System-based approach has been integrated via Digital Shearlet Transform, to make full utilization of perceptual watermarking. The highest energy Maximum Noise Fraction Eigen image has been selected via entropy calculation followed by impregnation of the watermark inside the highest energy first Eigen image returned by Maximum Noise Fraction, using a total insertion based approach. An efficient watermarking approach is always a trade-off between imperceptibility and robustness. A reliable metaheuristic optimization approach, namely the Bat algorithm has been incorporated to find the optimum embedding factor, which provides high robustness while maintaining sublime imperceptibility. Moreover, the watermark’s security has further been improved by encrypting it with a novel Hénon chaotic system-based cryptic algorithm. Qualitative and quantitative comparison with other state-of-the-art methods is a proof of the primacy of the proposed framework under most intentional and unintentional malicious impairments.