A Multiobjective Evolutionary Algorithm for Hyperspectral Image Watermarking

With the increasing availability of internet access to remote sensing imagery, the concern with image authentication and ownership issues is growing in the remote sensing community. Watermarking techniques help to solve the problems raised by this issue. In this paper we elaborate on the proposition of an optimal placement of the watermark image in a hyperspectral image. We propose an evolutionary algorithm for the digital semi-fragile watermaking of hyperspectral images based on the manipulation of the image discrete cosine transform (DCT) computed for each band in the image. The algorithm searches for the optimal localization in the support of an image’s DCT to place the mark image. The problem is stated as a multi-objective optimization problem (MOP), that involves the simultaneous minimization of distortion and robustness criteria. We propose appropriate fitness functions that implement these conflicting criteria, and that can be efficiently evaluated. The application of an evolutionary algorithm (MOGA) to the optimal watermarking hyperspectral images is presented. Given an appropriate initialization, the algorithm can perform the search for the optimal mark placement in the order of minutes, approaching real time application restrictions.