A Comparative Study Of Well-known Svd-based Image Watermarking

The Singular Value Decomposition (SVD) is one of the most useful tools of linear algebra having several applications in image processing, and more recently in digital watermarking. In this paper, we compare between three different and well-known approaches using SVD transformation to embed a watermark in digital images. Experimental results show that these schemes maintain high quality watermarked images and robustness against several conventional attacks. We also pointed out some weaknesses of these methods and some solutions proposed by other researchers.