High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion

Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded...

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Bibliographic Details
Main Authors: Fei Wang, Zhaoxin Xie, Zuo Chen
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/656251
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spelling doaj-129b075475594c098774db061448c39e2020-11-24T21:55:19ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/656251656251High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error ExpansionFei Wang0Zhaoxin Xie1Zuo Chen2School of Information Science and Engineering, Hunan University, Lushan South Rood, Changsha 410082, ChinaCollege of Computer Science and Technology, Zhejiang University, Hangzhou 310027, ChinaSchool of Information Science and Engineering, Hunan University, Lushan South Rood, Changsha 410082, ChinaBeing reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.http://dx.doi.org/10.1155/2014/656251
collection DOAJ
language English
format Article
sources DOAJ
author Fei Wang
Zhaoxin Xie
Zuo Chen
spellingShingle Fei Wang
Zhaoxin Xie
Zuo Chen
High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion
The Scientific World Journal
author_facet Fei Wang
Zhaoxin Xie
Zuo Chen
author_sort Fei Wang
title High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion
title_short High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion
title_full High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion
title_fullStr High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion
title_full_unstemmed High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion
title_sort high capacity reversible watermarking for audio by histogram shifting and predicted error expansion
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
description Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.
url http://dx.doi.org/10.1155/2014/656251
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AT zhaoxinxie highcapacityreversiblewatermarkingforaudiobyhistogramshiftingandpredictederrorexpansion
AT zuochen highcapacityreversiblewatermarkingforaudiobyhistogramshiftingandpredictederrorexpansion
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