scholarly journals High Capacity Reversible Data Hiding in Encrypted JPEG Images by Quadtree Compression and Prediction Error

Author(s):  
Aiswarya Mohan
Computers ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 152
Author(s):  
Ching-Yu Yang ◽  
Ja-Ling Wu

During medical treatment, personal privacy is involved and must be protected. Healthcare institutions have to keep medical images or health information secret unless they have permission from the data owner to disclose them. Reversible data hiding (RDH) is a technique that embeds metadata into an image and can be recovered without any distortion after the hidden data have been extracted. This work aims to develop a fully reversible two-bit embedding RDH algorithm with a large hiding capacity for medical images. Medical images can be partitioned into regions of interest (ROI) and regions of noninterest (RONI). ROI is informative with semantic meanings essential for clinical applications and diagnosis and cannot tolerate subtle changes. Therefore, we utilize histogram shifting and prediction error to embed metadata into RONI. In addition, our embedding algorithm minimizes the side effect to ROI as much as possible. To verify the effectiveness of the proposed approach, we benchmarked three types of medical images in DICOM format, namely X-ray photography (X-ray), computer tomography (CT), and magnetic resonance imaging (MRI). Experimental results show that most of the hidden data have been embedded in RONI, and the performance achieves high capacity and leaves less visible distortion to ROIs.


Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 664
Author(s):  
Ya Liu ◽  
Guangdong Feng ◽  
Chuan Qin ◽  
Haining Lu ◽  
Chin-Chen Chang

Nowadays, more and more researchers are interested in reversible data hiding in encrypted images (RDHEI), which can be applied in privacy protection and cloud storage. In this paper, a new RDHEI method on the basis of hierarchical quad-tree coding and multi-MSB (most significant bit) prediction is proposed. The content owner performs pixel prediction to obtain a prediction error image and explores the maximum embedding capacity of the prediction error image by hierarchical quad-tree coding before image encryption. According to the marked bits of vacated room capacity, the data hider can embed additional data into the room-vacated image without knowing the content of original image. Through the data hiding key and the encryption key, the legal receiver is able to conduct data extraction and image recovery separately. Experimental results show that the average embedding rates of the proposed method can separately reach 3.504 bpp (bits per pixel), 3.394 bpp, and 2.746 bpp on three well-known databases, BOSSBase, BOWS-2, and UCID, which are higher than some state-of-the-art methods.


2010 ◽  
Vol 90 (11) ◽  
pp. 2911-2922 ◽  
Author(s):  
Wien Hong ◽  
Tung-Shou Chen ◽  
Yu-Ping Chang ◽  
Chih-Wei Shiu

2018 ◽  
Vol 12 (12) ◽  
pp. 1-17 ◽  
Author(s):  
Chin-Cheng Chang ◽  
◽  
Ran Tang ◽  
Chia-Chen Lin ◽  
Wan-Li Lyu

2018 ◽  
Vol 30 (10) ◽  
pp. 1954
Author(s):  
Xiangguang Xiong ◽  
Yongfeng Cao ◽  
Weihua Ou ◽  
Bin Liu ◽  
Li Wei ◽  
...  

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