Robust double encryption and watermarking algorithms for color watermark images

Abstract

Current digital watermarking technologies mainly focus on the imperceptibility and robustness of watermark embedding, while the security of watermarking images is also worth further research. Considering nonlinear characteristics and the integration structure of storage and computation, memristors can be introduced into encryption algorithms to improve the effect of encryption. The paper proposes a double encryption algorithm for color watermark images based on MCNN (Memristive Cellular Neural Networks) and Arnold transform, generates chaotic sequences for watermark image encryption by introducing memristors to the CNN (Cellular Neural Networks) to construct MCNN, scrambles the images using the Arnold transform to achieve the double encryption of pixel values and pixel positions, and enhances the security of the watermark images. Adopting the SE (Spectral Entropy) complexity algorithm optimizes the parameters of MCNN, and improves the performance of the double encryption algorithm. The embedding and extraction of the encrypted watermark image is realized by the algorithm combining CT (Contourlet Transform) and SVD (Singular Value Decomposition), which enhances the ability to resist common attacks such as compression and rotation attacks. Experiment results show the proposed algorithms can better maintain the quality of the color watermark images, break the statistical characteristics of the original images, and the generated key has good randomness. In addition, the presented algorithms are highly sensitive to the key, and improve the ability to resist statistical attacks, differential attacks, exhaustive attacks and common image attacks with good security, robustness and imperceptibility.