Paper Info
Title
Optimal Reversible Data Hiding Scheme Based on Multiple Histograms Modification
Abstract
AbstractRecently, a method based on multiple histograms modification (MHM) is proposed for reversible data hiding (RDH), in which a sequence of prediction-error histograms are generated and two expansion bins are selected in each histogram for expansion embedding. However, although efficient, it only chooses a single pair of expansion bins which limits the embedding capacity. On the other hand, the exhaustive expansion-bin-selection procedure in MHM takes huge computation time, so that it cannot be extended for high capacity RDH. In order to overcome the aforementioned drawbacks, an optimal RDH scheme based on MHM for high capacity embedding is proposed in this paper. First, to improve the embedding capacity, instead of a single pair of expansion bins, multiple pairs of expansion bins are utilized for each histogram, and the multiple-expansion-bin-selection for optimal embedding is formulated as an optimization problem. Then, unlike the exhaustive searching way used in MHM, a computationally efficient algorithm is proposed to solve the optimization problem, so that the optimal expansion bins can be adaptively determined to optimize the embedding performance. By the proposed approach, high embedding capacity can be achieved with good marked image quality, and the experimental results show that it is better than the original MHM and some other state-of-the-art methods.
Year
DOI
Venue
2020
10.1109/TCSVT.2019.2942489
Periodicals
Keywords
DocType
Volume
Histograms, Complexity theory, Optimization, Distortion, Image quality, Image restoration, Information science, Reversible data hiding, histogram shifting, prediction-error expansion, multiple histograms modification, high capacity embedding
Journal
30
Issue
ISSN
Citations 
8
1051-8215
11
PageRank 
References 
Authors
0.45
0
4
Name
Order
Citations
PageRank
Wenfa Qi1224.13
Xiaolong Li22264114.79
Tong Zhang35318.56
Zongming Guo477881.98