# An Improved Reversible Data Hiding in Encrypted Images using Parametric Binary Tree Labeling

## TL;DR

This paper introduces an improved reversible data hiding method in encrypted images using parametric binary tree labeling, which enhances embedding capacity while allowing lossless recovery of the original image and secret data.

## Contribution

It presents a novel IPBTL-RDHEI scheme that leverages spatial correlation across the entire image for higher embedding rates compared to existing methods.

## Key findings

- Achieves higher embedding rate than state-of-the-art methods
- Allows lossless recovery of original image and secret data
- Outperforms competitors in experimental evaluations

## Abstract

This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image but not in small image blocks to reserve room for hiding data. Then the original image is encrypted with an encryption key and the parametric binary tree is used to label encrypted pixels into two different categories. Finally, one of the two categories of encrypted pixels can embed secret information by bit replacement. According to the experimental results, compared with several state-of-the-art methods, the proposed IPBTL-RDHEI method achieves higher embedding rate and outperforms the competitors. Due to the reversibility of IPBTL-RDHEI, the original plaintext image and the secret information can be restored and extracted losslessly and separately.