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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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 |
work_keys_str_mv |
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1725863459361390592 |