High capacity reversible data hiding in encrypted images based on adaptive quadtree partitioning and MSB prediction

Abstract

To improve the embedding capacity of reversible data hiding in encrypted images (RDH-EI), a new RDH-EI scheme is proposed based on adaptive quadtree partitioning and most significant bit (MSB) prediction. First, according to the smoothness of the image, the image is partitioned into blocks based on adaptive quadtree partitioning, and then blocks of different sizes are encrypted and scrambled at the block level to resist the analysis of the encrypted images. In the data embedding stage, the adaptive MSB prediction method proposed by Wang and He (2022) is improved by taking the upper-left pixel in the block as the target pixel, to predict other pixels to free up more embedding space. To the best of our knowledge, quadtree partitioning is first applied to RDH-EI. Simulation results show that the proposed method is reversible and separable, and that its average embedding capacity is improved. For gray images with a size of 512×512, the average embedding capacity is increased by 25 565 bits. For all smooth images with improved embedding capacity, the average embedding capacity is increased by about 35 530 bits.

摘要

为提高密文域可逆信息隐藏(reversible data hiding in encrypted images, RDH-EI)算 法的嵌入容量, 提出一种基于自适应四叉树分块和最高有效位(most significant bit, MSB)预测的大容量RDH-EI方案。首先根据图像的平滑程度进行自适应四叉树分块, 然后将不同大小的块进行块级加密和置乱, 以抵抗对于加密图像的分析。在嵌入数据阶段, 对于文献Wang & He(2022)提出的自适应MSB预测方法进行改进, 以块中左上角像素为目标像素, 用于预测其它像素, 从而腾出更多嵌入空间。首次将四叉树分块方法应用于密文域图像的可逆信息隐藏。模拟结果表明, 所提方法具有可逆性与可分离性, 并且在自适应MSB预测 方法基础上进一步提高了平均嵌入容量。对于512×512大小的灰度图像, 平均嵌入容量提高约25 565比特, 对于所有嵌入容量有所提高的较平滑图像, 平均嵌入容量提高约35 530比特。