Title
A Novel Difference Expansion Transform for Reversible Data Embedding
Abstract
Reversible data embedding theory has marked a new epoch for data hiding and information security. Being reversible, the original data and the embedded data should be completely restored. Difference expansion transform is a remarkable breakthrough in reversible data-hiding schemes. The difference expansion method achieves high embedding capacity and keeps distortion low. This paper shows that the difference expansion method with the simplified location map and new expandability can achieve more embedding capacity while keeping the distortion at the same level as the original expansion method. Performance of the proposed scheme in this paper is shown to be better than the original difference expansion scheme by Tian and its improved version by Kamstra and Heijmans. This improvement can be possible by exploiting the quasi-Laplace distribution of the difference values.
Year
DOI
Venue
2008
10.1109/TIFS.2008.924600
IEEE Transactions on Information Forensics and Security
Keywords
Field
DocType
original data,original difference expansion scheme,reversible data embedding,reversible data,original expansion method,novel difference expansion transform,embedded data,difference value,difference expansion,embedding capacity,difference expansion method,high embedding capacity,image quality,image restoration,data hiding,pixel,information security,laplace distribution,degradation,payloads
Location map,Embedding,Pattern recognition,Computer science,Information hiding,Algorithm,Image quality,Theoretical computer science,Pixel,Artificial intelligence,Image restoration,Distortion
Journal
Volume
Issue
ISSN
3
3
1556-6013
Citations 
PageRank 
References 
128
5.15
13
Authors
5
Search Limit
100128
Name
Order
Citations
PageRank
Hyoung-Joong Kim1129581.25
V. Sachnev21285.15
Yun Qing Shi351823.34
Je-Ho Nam444023.94
Hyon-Gon Choo51348.25