Image Watermarking Based on Chaos Encryption with Hybrid Mapping and Grey Wolf Optimizer
International journal of intelligent engineering and systems · 2021
In this study, a new watermarking system was proposed to address two major concerns: slow learning and computational capability.At first, cover image was transformed into wavelet environment utilizing Integer Wavelet Transform (IWT) that makes the cover image free from false errors.Then, Grey Wolf Optimizer (GWO) was utilized for selecting the image pixels to embed the secret image in the cover image.GWO effectively selects the pixels utilizing fitness function, which calculates entropy, pixel intensity and edge of the cover images.Besides, the secret image was encrypted by using chaos encryption with hybrid mapping (logistic and henon map) that improves computation efficiency and security with good embedding capacity.After the cover image transformation and secret image encryption, Least Significant Bit (LSB) was utilized to deliver self-recovery features and also for locating the tempered region in the digital image.Experimental results showed that the developed system attained a secure transmission network with low complexity in light of Unified Averaged Changed Intensity (UACI), entropy value, Structural Similarity Index (SSIM), Normalized Cross Correlation (NCC), and Peak Signal-to-Noise Ratio (PSNR).Compared to the existing systems, the proposed system showed 3dB to 4.4 dB improvement in PSNR and 0.32 value improvement in SSIM.