Algorithm Research Of The Image Digital Watermarking And The Quality Assessment Based On The HVS

In the past few years, with the development of the internet and multimedia technology, the production, copy and transmission of the visual content has become more and more easily. So the copyright protection of the visual content has become a critical issue in the recent years. The digital watermarking technology which has been considered as an efficient solution to the copyright protection problem is getting more and more attention by the researchers. Generally speaking, the copyright information which to be embedded into the visual content must have high robustness. Additionally, the procedure of the information embedding should keep the quality of visual content.In general, it is a conflicting issue to make a good balance between the robustness and the transparency of the digital watermarking system. In order to solve this problem, we proposed a novel digital watermarking algorithm based on the JND (Just Noticeable Distortion) model in balanced multiwavelet domain. First, according to the properties of the human visual system, a novel multiresolution JND model is constructed in balanced multiwavelet domain. This model incorporates the spatial CSF (Contrast Sensitivity Function), the luminance self-adaptation masking, and the contrast masking effect via separating the sharp edge and the texture. Then, based on this model, the watermark is adaptively inserted into the visual redundancy areas of the luminance and chrominance components without introducing the perceivable distortions. Experimental results show that the proposed watermarking scheme is transparent and has a high robustness to various attacks.In addition, to solve the problem of the low powerful of the traditional image quality metric such as PNSR to evaluate the transparency of the digital watermarking system, we developed a novel full reference image quality assessment method using the properties of the human visual system. In the proposed scheme, the Gabor wavelet transform is first applied to the image, then DNT (Divisive Normalization Transform) is applied to the Gabor features to mimic the suppression effect of the neighboring simple cells to the center simple cell with respect to the visual response. Finally, the mutual information between the visual energy information of the reference and distorted image is used as an indicator to predict the visual quality of the image. Experiment results show that the objective quality of the images which predicted by our algorithm has a high correlation with the subjective quality of the images.