@Article{cmc.2020.09723,
AUTHOR = {Lingfeng Qu, Hongjie He, Shanjun Zhang, Fan Chen},
TITLE = {Reversible Data Hiding in Encrypted Images Based on Prediction  and Adaptive Classification Scrambling},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {65},
YEAR = {2020},
NUMBER = {3},
PAGES = {2623--2638},
URL = {http://www.techscience.com/cmc/v65n3/40191},
ISSN = {1546-2226},
ABSTRACT = {Reversible data hiding in encrypted images (RDH-EI) technology is widely 
used in cloud storage for image privacy protection. In order to improve the embedding 
capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed 
a reversible data hiding algorithm for encrypted images based on prediction and adaptive 
classification scrambling. First, the prediction error image is obtained by a novel 
prediction method before encryption. Then, the image pixel values are divided into two 
categories by the threshold range, which is selected adaptively according to the image 
content. Multiple high-significant bits of pixels within the threshold range are used for 
embedding data and pixel values outside the threshold range remain unchanged. The 
optimal threshold selected adaptively ensures the maximum embedding capacity of the 
algorithm. Moreover, the security of encrypted images can be improved by the 
combination of XOR encryption and classification scrambling encryption since the 
embedded data is independent of the pixel position. Experiment results demonstrate that 
the proposed method has higher embedding capacity compared with the current state-ofthe-art methods for images with different texture complexity.},
DOI = {10.32604/cmc.2020.09723}
}