Efficient Reversible Data Hiding Algorithms Based on Dual Prediction

TL;DR

This paper introduces a reversible data hiding algorithm utilizing dual predictors and histogram shifting, enhancing embedding capacity without extra overhead and maintaining image quality.

Contribution

It extends the MPE algorithm by incorporating two predictors and histogram bins, improving embedding capacity while avoiding additional communication overhead.

Findings

Using two predictors boosts embedding capacity.

The algorithm maintains competitive image quality.

Extending to multiple histogram bins increases capacity.

Abstract

In this paper, a new reversible data hiding (RDH) algorithm that is based on the concept of shifting of prediction error histograms is proposed. The algorithm extends the efficient modification of prediction errors (MPE) algorithm by incorporating two predictors and using one prediction error value for data embedding. The motivation behind using two predictors is driven by the fact that predictors have different prediction accuracy which is directly related to the embedding capacity and quality of the stego image. The key feature of the proposed algorithm lies in using two predictors without the need to communicate additional overhead with the stego image. Basically, the identification of the predictor that is used during embedding is done through a set of rules. The proposed algorithm is further extended to use two and three bins in the prediction errors histogram in order to increase the embedding capacity. Performance evaluation of the proposed algorithm and its extensions showed the advantage of using two predictors in boosting the embedding capacity while providing competitive quality for the stego image.