Watermarking with knowledge of image database

The goal of this paper is to study how a-prior knowledge of the image database could be exploited for better watermarking performance. Unlike most formulations, where the encoder and detector only know the distribution of the images, under our formulation, the actual set of images to be watermarked are known, either in a static or dynamic setting. To achieve better performance, instead of choosing a random watermarking key or predefined code-book as is the usual practice, we derive the watermarking keys from the database. We study two settings, static and dynamic. In the dynamic setting, the image database starts from a single image and grows as more images arrive. Thus the watermarking keys have to be updated frequently. This setting can be applied to applications where the detector has access to the Internet. To demonstrate the main idea, we extend a variant of spread-spectrum method to a few schemes, and analyze their performance. Interestingly, the requirements on false-alarm, robustness and distortion can be traded-off with the size of the watermarking keys. We perform our experiments on both natural images and Gaussian source. Our analysis and experiments show promising improvement in performance by exploiting the a-prior knowledge of the image database, specifically for fixed robustness and false alarm we achieve significant reduction of distortion. Similar idea can be incorporated into other watermarking methods.