Separable and Reversible Data Hiding in Encrypted Images Using Parametric Binary Tree Labeling

Abstract

This paper first introduces a parametric binary tree labeling scheme (PBTL) to label image pixels in two different categories. Using PBTL, a data embedding method (PBTL–DE) is proposed to embed secret data to an image by exploiting spatial redundancy within small image blocks. We then apply PBTL–DE into the encrypted domain and propose a PBTL-based reversible data hiding method in encrypted images (PBTL–RDHEI). PBTL–RDHEI is a separable and reversible method that both the original image and secret data can be recovered and extracted losslessly and independently. Experiment results and analysis show that PBTL–RDHEI is able to achieve an average embedding rate as large as 1.752\xa0bpp and 2.003\xa0bpp when block size is set to <inline-formula><tex-math notation= LaTeX >$2\\times 2$</tex-math></inline-formula> and <inline-formula><tex-math notation= LaTeX >$3\\times 3$</tex-math></inline-formula>, respectively.