A DCT-domain system for robust image watermarking
Signal Processing
Digital watermarking
Hybrid KLT-SVD image compression
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Robust DWT-SVD domain image watermarking: embedding data in all frequencies
Proceedings of the 2004 workshop on Multimedia and security
SVD-based digital image watermarking scheme
Pattern Recognition Letters
An SVD-based watermarking scheme for protecting rightful ownership
IEEE Transactions on Multimedia
DCT-based image watermarking using subsampling
IEEE Transactions on Multimedia
On the security of an SVD-based ownership watermarking
IEEE Transactions on Multimedia
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Improved wavelet-based watermarking through pixel-wise masking
IEEE Transactions on Image Processing
A wavelet-based watermarking algorithm for ownership verification of digital images
IEEE Transactions on Image Processing
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Digital watermarking is a technique for protecting the copyright of intellectual property. In the recent past, several watermarking schemes have been proposed that modify pixel intensity values or coefficient values in transform domain. The popular transform domains are DCT, DFT, DWT and Singular Value Decomposition (SVD). This paper presents a highly robust and oblivious digital image watermarking scheme, in the SVD domain using dither quantization. SVD of a given image block results in three matrices [U D V]. The proposed method integrates the approach of SVD based digital watermarking scheme and dither quantization. Dither quantization, a variant of Quantization Index Modulation (QIM) is used to modify the largest component of Diagonal Matrix (D) for watermark embedding. The proposed algorithm is more secure for data hiding and robust to various attacks, viz., JPEG2000 compression, JPEG compression, rotation, scaling, cropping, row-column blanking, row-column copying, salt & pepper noise, filtering, gamma correction and image tampering. Superior experimental results are observed in the proposed algorithm over Sun et al. scheme [1]. Normalized cross correlation (NC) and Peak Signal to Noise Ratio (PSNR) are used to test and verify the robustness of the proposed algorithm.