Digital watermarking
Optimal transform domain watermark embedding via linear programming
Signal Processing - Special section on information theoretic aspects of digital watermarking
Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics
A Stochastic Approach to Content Adaptive Digital Image Watermarking
IH '99 Proceedings of the Third International Workshop on Information Hiding
Convex Optimization
Digital Watermarking and Steganography
Digital Watermarking and Steganography
Wet paper codes with improved embedding efficiency
IEEE Transactions on Information Forensics and Security
A Set Theoretic Framework for Watermarking and Its Application to Semifragile Tamper Detection
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Information Theory
Information-theoretic analysis of information hiding
IEEE Transactions on Information Theory
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Set theoretic signal restoration using an error in variables criterion
IEEE Transactions on Image Processing
Robust image-adaptive data hiding using erasure and error correction
IEEE Transactions on Image Processing
Lossless watermarking for image authentication: a new framework and an implementation
IEEE Transactions on Image Processing
Projection-based spatially adaptive reconstruction of block-transform compressed images
IEEE Transactions on Image Processing
Digital Image Authentication: A Review
International Journal of Digital Library Systems
Reversible watermarking scheme for medical image based on differential evolution
Expert Systems with Applications: An International Journal
A wavelet-based particle swarm optimization algorithm for digital image watermarking
Integrated Computer-Aided Engineering - Anniversary Volume: Celebrating 20 Years of Excellence
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We consider optimal formulations of spread spectrum watermark embedding where the common requirements of watermarking, such as perceptual closeness of the watermarked image to the cover and detectability of the watermark in the presence of noise and compression, are posed as constraints while one metric pertaining to these requirements is optimized. We propose an algorithmic framework for solving these optimal embedding problems via a multistep feasibility approach that combines projections onto convex sets (POCS) based feasibility watermarking with a bisection parameter search for determining the optimum value of the objective function and the optimum watermarked image. The framework is general and can handle optimal watermark embedding problems with convex and quasi-convex formulations of watermark requirements with assured convergence to the global optimum. The proposed scheme is a natural extension of set-theoretic watermark design and provides a link between convex feasibility and optimization formulations for watermark embedding. We demonstrate a number of optimal watermark embeddings in the proposed framework corresponding to maximal robustness to additive noise, maximal robustness to compression, minimal frequency weighted perceptual distortion, and minimal watermark texture visibility. Experimental results demonstrate that the framework is effective in optimizing the desired characteristic while meeting the constraints. The results also highlight both anticipated and unanticipated competition between the common requirements for watermark embedding.