Vector quantization and signal compression
Vector quantization and signal compression
The role of information theory in watermarking and its application to image watermarking
Signal Processing - Special section on information theoretic aspects of digital watermarking
IEEE Transactions on Signal Processing
Scalar Costa scheme for information embedding
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Lattice codebook enumeration for generalized Gaussian source
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
A class of authentication digital watermarks for secure multimedia communication
IEEE Transactions on Image Processing
Analysis and design of watermarking algorithms for improved resistance to compression
IEEE Transactions on Image Processing
Applying informed coding and embedding to design a robust high-capacity watermark
IEEE Transactions on Image Processing
Joint security and robustness enhancement for quantization based data embedding
IEEE Transactions on Circuits and Systems for Video Technology
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The design of a variable rate joint watermaking and compression (JWC) scheme is examined in this paper. The proposed approach, called modulated lattice vector quantization (MLVQ), is based on dither modulation quantization index modulation (DM-QIM) which allows for embedding information while maintaining good coding performance. In the first part, we propose a specific indexing method to make MLVQ with a multidimensional codebook feasible. Furthermore, a quantization parameter estimation was designed to ensure the invertibility of the embedding. The limitations of the compression performance of JWC schemes are studied in the second part. We show the existence of a coding rate lower bound which depends mainly on the codebook characteristics and dramatically decreases coding performance. To circumvent this drawback, two improved MLVQ schemes are proposed. In the first one, called arbitrary MLVQ, the embedding is performed on part of the signal to ensure a low embedding/coding ratio. In the second one, called deadzone MLVQ, the coding efficiency is further improved by maintaining the sparsity of the quantized host signal. It consists in excluding the sparse signal components from the embedding process then thresholding them. These schemes both applying wavelet coding demonstrate their efficiency as variable rate coders.