Multilayer Reversible Information Hiding with Prediction-Error Expansion and Dynamic Threshold Analysis

Sensors (Basel). 2022 Jun 28;22(13):4872. doi: 10.3390/s22134872.

Abstract

The rapid development of internet and social media has driven the great requirement for information sharing and intelligent property protection. Therefore, reversible information embedding theory has marked some approaches for information security. Assuming reversibility, the original and embedded data must be completely restored. In this paper, a high-capacity and multilayer reversible information hiding technique for digital images was presented. First, the integer Haar wavelet transform scheme converted the cover image from the spatial into the frequency domain that was used. Furthermore, we applied dynamic threshold analysis, the parameters of the predicted model, the location map, and the multilayer embedding method to improve the quality of the stego image and restore the cover image. In comparison with current algorithms, the proposed algorithm often had better embedding capacity versus image quality performance.

Keywords: dynamic threshold analysis; high-capacity; multilayer; predicted parameters adjustment; reversible information hiding.

Grants and funding

This research received no external funding.