Efficient Joint Coding and Reversible Data Hiding for AMBTC Images Using Comprehensive Prediction and Dynamic Encoding

• Wien Hong,
• Yi-Hua Liu,
• Guan-Zhong Su,
• Xiaoyu Zhou,
• Tung-Shou Chen,

Vol. 19, No. 9, September 30, 2025
10.3837/tiis.2025.09.013, Download Paper (Free):

• AMBTC
• Reversible data hiding
• predictive coding

Abstract

The Absolute Moment Block Truncation Coding (AMBTC) compresses image blocks into domains that describe the statistical properties of the image, and a bitmap that describes the texture. Previous methods for joint coding and reversible data hiding of AMBTC images mostly involved obtaining prediction errors of the domains and then adjusting the range of intervals of prediction errors through parameters to optimize encoding efficiency. However, they ignored the correlation between domains when predicting, leading to limited accuracy. Additionally, these methods did not consider the space required for prediction errors when dividing intervals, necessitating the use of leading zeros for their recording. In this paper, we propose a Comprehensive Predictor (CP) to enhance prediction accuracy by utilizing the linear correlation between domains. Moreover, we introduce the One’s Complement Encoding (OCE) and Dynamic Indicator Sorting (DIS) techniques, enabling the interval of prediction errors to be recorded without leading zeros. According to the experimental results, when compared to state-of-the-art methods, our method can achieve an average bitrate reduction of 5.14%.

Statistics

Cite this article