Watermarking System Using DWT and SVD

Information hiding has garnered significant attention from researchers over the past two decades, due to its growing importance in securing visual applications. As a consequence, watermarking has become a focal point in numerous studies for its ability to protect sensitive data from unauthorized access, copying, manipulation, and infringement of copyrights or property rights. Watermarks can be applied to a wide range of mediums, including texts, documents, books, audio, video, and images. Various watermarking techniques exist, such as the discrete Fourier transform (DFT), the discrete cosine transform (DCT), the discrete wavelet transform (DWT), the singular value decomposition (SVD), deep learning, and other more methods, each of which has its own set of benefits and drawbacks. In this paper, we propose a novel algorithm that combines the strengths of both SVD and DWT approaches to enhance watermarking performance. This innovative watermarking technique yields accurate results and has demonstrated exceptional performance metrics, as evidenced by signal-to-noise ratio (SNR) and peak signal-to-noise ratio (PSNR) measurements.