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Related Experiment Video

Updated: Nov 6, 2025

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

Reversible Data Hiding Based on Dual Pairwise Prediction-Error Expansion.

Wenguang He, Zhanchuan Cai

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|May 12, 2021

Summary

A new dual pairwise prediction-error expansion (PEE) strategy improves reversible data hiding. This method enhances capacity-distortion performance by better exploiting error correlations in digital images.

Related Experiment Videos

Last Updated: Nov 6, 2025

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

Area of Science:

Computer Science
Information Security
Digital Image Processing

Background:

Reversible data hiding techniques leverage cover medium redundancy.
Prediction-error expansion (PEE) is a highly effective mechanism for data hiding.
Existing pairwise PEE methods offer improvements but have limitations in exploiting error correlations.

Purpose of the Study:

To introduce a novel dual pairwise PEE strategy for enhanced reversible data hiding.
To improve the capacity-distortion performance of existing pairwise PEE methods.
To fully exploit the potential of pairwise PEE by addressing its limitations.

Main Methods:

Proposing a dual pairwise PEE strategy that recalculates and collects pairing errors.
Forming an error sequence after shifting individual pairing errors.
Creating new error-pairs from neighboring errors in the sequence for double pairwise PEE.

Main Results:

The dual pairwise PEE significantly exploits error correlations more effectively than original pairwise PEE.
The proposed scheme achieves superior capacity-distortion performance.
Experimental results show the scheme outperforms several state-of-the-art methods.

Conclusions:

The dual pairwise PEE strategy offers a significant advancement in reversible data hiding.
This method provides a better balance between data hiding capacity and image distortion.
The proposed approach represents a state-of-the-art solution in the field.