An Enhanced Informed Watermarking Scheme Using the Posterior Hidden Markov Model

Abstract

Designing a practical watermarking scheme with high robustness, feasible imperceptibility, and large capacity remains one of the most important research topics in robust watermarking. This paper presents a posterior hidden Markov model (HMM-) based informed image watermarking scheme, which well enhances the practicability of the prior-HMM-based informed watermarking with favorable robustness, imperceptibility, and capacity. To make the encoder and decoder use the (nearly) identical posterior HMM, each cover image at the encoder and each received image at the decoder are attacked with JPEG compression at an equivalently small quality factor (QF). The attacked images are then employed to estimate HMM parameter sets for both the encoder and decoder, respectively. Numerical simulations show that a small QF of 5 is an optimum setting for practical use. Based on this posterior HMM, we develop an enhanced posterior-HMM-based informed watermarking scheme. Extensive experimental simulations show that the proposed scheme is comparable to its prior counterpart in which the HMM is estimated with the original image, but it avoids the transmission of the prior HMM from the encoder to the decoder. This thus well enhances the practical application of HMM-based informed watermarking systems. Also, it is demonstrated that the proposed scheme has the robustness comparable to the state-of-the-art with significantly reduced computation time.