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An enhanced informed watermarking scheme using the posterior hidden Markov model.

¹College of Information, South China Agricultural University, Guangzhou 510642, China ; School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510275, China.

Thescientificworldjournal

|February 28, 2014

Summary

This study introduces a practical image watermarking scheme using a posterior Hidden Markov Model (HMM). It achieves robust watermarking with improved imperceptibility and capacity, enhancing real-world applications.

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Area of Science:

Digital Image Processing
Information Security
Signal Processing

Background:

Robust watermarking schemes are crucial for data security.
Existing informed watermarking methods face practical limitations.

Purpose of the Study:

To develop a practical posterior Hidden Markov Model (HMM)-based informed image watermarking scheme.
To enhance robustness, imperceptibility, and capacity compared to prior methods.

Main Methods:

Utilized JPEG compression with a small Quality Factor (QF=5) to estimate HMM parameters at both encoder and decoder.
Developed an enhanced posterior-HMM-based informed watermarking scheme.

Main Results:

The proposed scheme achieves comparable robustness to state-of-the-art methods.
It significantly reduces computation time and avoids transmitting prior HMM information.
Achieved favorable robustness, imperceptibility, and capacity.

Conclusions:

The posterior HMM-based scheme enhances the practicality of informed watermarking systems.
The method offers a robust, efficient, and practical solution for digital image watermarking.