Performance Enhancement for DWT-HMM Image Watermarking with Content-Adaptive Approach
A DWT-HMM (hidden Markov model in wavelet domain) image watermarking algorithm with content-adaptive approach is proposed in this paper to optimized the trade-off between robustness and visual quality, which is characterized as follows: the entropy mask proposed by Watson is constructed in wavelet domain; the entropy mask and the new developed integrated HVS are used as the measures to adaptively select image components for watermarking; repeat-accumulation (RA) code with erasure and error correction is employed to synchronize the watermarked image; and a posterior HMM is utilized in watermark detection. Considerable improvement in robustness performance with the proposed adaptive algorithm is obtained over the previous DWT-HMM watermarking algorithm with stochastic embedding.