JND-Guided Perceptually Color Image Watermarking in Spatial Domain

Abstract

Watermarking is an effective solution for copyright protection and forensics tracking via hiding information into the image signal. Recently, spatial-embedding watermarking methods from different transform domain have been proposed rapidly and effectively protect the copyright of the color image. Compared to the individual frequency domain method, it has both advantages of spatial domain and frequency domain. Here, we proposed a novel spatial-embedding watermarking method based on an attended just noticeable difference (JND) model with color complexity, to achieve a good tradeoff between robustness and perceptual quality. In particular, at the spatial embedding level, the direct current (DC) coefficients are selected for embedding and the perceptual JND model is used to guide the amount of pixel modification to improve visual quality. Different from the previous JND model, we proposed an attended JND model that considers color complexity, which is more consistent of the human visual perception model. Compared with the other JND models, the proposed JND model is more suitable for the watermarking framework. Experimental results show that the proposed watermarking scheme has better performance than other existing watermarking schemes. This greatly benefits the practical implementations of the spatial-embedding watermarking methods.