A combined SVD-DWT watermarking scheme with multi-level compression using sampling and quantization on DCT followed by PCA

Abstract

This paper proposes a watermarking scheme, which combine both singular value decomposition (SVD) and discrete wavelet transform (DWT) based watermarking techniques. In addition to this, the paper introduces multilevel compression on the watermark image to improve the visual quality of the watermarked image. This can be achieved in two levels. In first level, compression is done by applying sampling and quantization on discrete cosine transform (DCT) coefficients. Then in the second level compression is carried out by principal component analysis (PCA). The proposed method is compared with various existing watermarking schemes by using image quality measures like peak signal to noise ratio (PSNR), mean structural similarity index (MSSIM) and correlation coefficient. It is observed that the proposed approach survives unintentional linear attacks such as rescaling, rotation and some minor modifications.