Abstract

This paper proposes a joint coding and reversible data hiding method for absolute moment block truncation coding (AMBTC) compressed images. Existing methods use a predictor to predict the quantization levels of AMBTC codes. Equal-length indicators, secret bits and prediction errors are concatenated to construct the output code stream. However, the quantization levels might not highly correlate with their neighbors for predictive coding, and the use of equal-length indicators might impede the coding efficiency. The proposed method uses reversible integer transform to represent the quantization levels by their means and differences, which is advantageous for predictive coding. Moreover, the prediction errors are better classified into symmetrical encoding cases using the adaptive classification technique. The length of indicators and the bits representing the prediction errors are properly assigned according to the classified results. Experiments show that the proposed method offers the lowest bitrate for a variety of images when compared with the existing state-of-the-art works.

Highlights

  • The rapid development of internet technology has made data security a key consideration for data transmission or content protection

  • While most digital data can be transmitted over the internet, transmitted data is exposed to the risks of illegal access or interception

  • We propose a new reversible data hiding (RDH) method for absolute moment block truncation coding (AMBTC) compressed codes

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Summary

Introduction

The rapid development of internet technology has made data security a key consideration for data transmission or content protection. While most digital data can be transmitted over the internet, transmitted data is exposed to the risks of illegal access or interception. A solution to these problems is to employ a data hiding method, in which secret data are embedded into a digital media to cover the presence of embedment, or to protect the transmitted contents. Data hiding methods for images can be classified into irreversible [1,2,3] and reversible [4,5,6,7] methods. The distortions of irreversible methods are permanent, and they are not suitable for applications where no distortions are allowed

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