Two-dimensional histogram modification based reversible data hiding using motion vector for H.264

Histogram modification (HM) is an efficient algorithm for reversible data hiding into H.264 video, motion vector based methods have been applied to HM. In this paper, we present a special strategy of reversible data hiding using motion vector based on two-dimensional histogram modification. Firstly,...

Full description

Saved in:
Bibliographic Details
Published in:Multimedia tools and applications 2019-04, Vol.78 (7), p.8167-8181
Main Authors: Li, Dong, Zhang, YingNan, Li, XinChao, Niu, Ke, Yang, XiaoYuan, Sun, YuJuan
Format: Article
Language:English
Subjects:
Algorithms
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Digital video
Embedding
Histograms
Multimedia computer applications
Multimedia Information Systems
Special Purpose and Application-Based Systems
Three dimensional motion
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Histogram modification (HM) is an efficient algorithm for reversible data hiding into H.264 video, motion vector based methods have been applied to HM. In this paper, we present a special strategy of reversible data hiding using motion vector based on two-dimensional histogram modification. Firstly, the two components of a motion vector will compose an embedding pair. The values of embedding pairs are classified into 17 non-intersect sets. Then, according to the set that the embedding pair belongs to, we can embed data into motion vectors by modifying the value of embedding pair. Experimental results verify that the embedding capacity is increased by two times compared with the previous algorithm, and the PSNR declines about 5%. The reversibility of the algorithm is also studied, three rules are presented to judge the reversibility of an algorithm directly, and the rules are suitable for other histogram modification based methods.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-018-6729-3