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 25565 bits. For all smooth images with improved embedding capacity, the average embedding capacity is increased by about 35530 bits.

Keywords

Adaptive quadtree partitioning / Adaptive most significant bit (MSB) prediction / Reversible data hiding in encrypted images (RDH-EI) / High embedding capacity

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2023 Zhejiang University Press