Hybrid Predictor Based Four-Phase Adaptive Reversible Watermarking

Reversible watermarking has gained importance due to increased involvement of digital media in sensitive fields, such as medical and law enforcement. We propose a prediction error expansion-based watermarking scheme that allows embedding reversible watermark in the image with low distortion. Researc...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access Vol. 6; pp. 13213 - 13230
Main Authors: Ishtiaq, Muhammad, Ali, Waqar, Shahzad, Waseem, Jaffar, Muhammad Arfan, Nam, Yunyoung
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.01.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive watermarking
Context
Digital media
Distortion
Distortion measurement
Embedding
error-expansion
Histograms
Image coding
Image enhancement
Payloads
prediction
reversible watermarking
Sorting
Watermarking
ISSN:2169-3536, 2169-3536
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Reversible watermarking has gained importance due to increased involvement of digital media in sensitive fields, such as medical and law enforcement. We propose a prediction error expansion-based watermarking scheme that allows embedding reversible watermark in the image with low distortion. Research work proposes four-phase representation of image which allows exploitation of larger prediction context. We have also proposed a hybrid predictor that helps enhance the prediction accuracy. To reduce image distortion at lower capacity payloads, we use sorting of estimated prediction errors through sorting of prediction context variances. For improvement at higher capacity payloads, adaptive embedding is used to determine whether to embed single or two bits in a given prediction error. The results are compared against some state-of-the-art techniques in the field and show promising results.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2803301