Αποδοτικές τεχνικές αντιστοίχισης και ψηφιακής υδατογράφησης εικόνων

Abstract

Image registration aims at finding geometrical or other differences between two or more images. Image watermarking offers copyright protection by embedding in the images an invisible signal, a watermark, in such a way that it is difficult to be removed. Image registration can be part of a watermark detector. Moreover, similar (or the same) similarity measures are used for both image registration and watermark detection. Thus, any improvement concerning the image registration or the similarity measures can have positive effects on image watermarking, too. Our research concerning the image registration problem deals with the spatial cross-correlation, which has the following drawback: the region around its maximum value can be rather wide, affecting the registration accuracy. This problem can be solved, by properly pre-whitening the images with the prediction error filter. Furthermore, an iterative algorithm is proposed for registering images with translation and rotation differences, which is then applied in sequences of medical images for cancer diagnosis. A second disadvantage of the spatial correlation is its computational cost. A fast computation scheme is proposed, based on a proper partitioning of the images and the Fourier transform. Also, the most computationally intensive part of a registration process is the evaluation of the involved measure for different relative image positions. Thus, an efficient iterative algorithm is developed that considerably reduces the number of searches required for finding the correlation coefficient maximum value and provides pixel accuracy. Finally, an image registration technique with subpixel accuracy is proposed, which is based on the correlation coefficient maximization. This technique does not require the reconstruction of the intensity values and provides a closed form solution to the subpixel translation estimation problem. As far as the problem of image watermarking is concerned, our research aims at embedding robust watermarks in spatial domain and improving their detection. First, a spatial perceptual mask is proposed, based on the local variance of the initial image prediction error. A blind detector is also developed, which performs better than the existing ones. This is theoretically proved for the general attack case with linear filter and noise. Furthermore, a new spatial perceptual mask is proposed that allows for a significantly increased strength of the watermark, while at the same time the image quality remains very good. Its performance is compared to known and widely used masks and is proved to be much better. Moreover, an improved detector is developed, which, combined with the new mask, performs very well. Finally, a new multiplicative watermark embedding is proposed, which uses space-time block coding (specifically a 4x4 real orthogonal design). This scheme is proved to perform much better than the repetitive watermarking.