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A multi-scale image watermarking based on integer wavelet transform and singular value decomposition

delete2021-04-01
delete44
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OA
AI
Y
Yuling Luo *
J
Junxiu Liu
L
Lvchen Cao
S
Shunsheng Zhang
S
Senhui Qiu
Y
Yi Cao
DOI:10.1016/j.eswa.2020.114272delete
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摘要

摘要

En 中文
Image watermarking technique is one of effective solutions to protect copyright, and it is applied to a variety of information security application domains. It needs to meet four requirements of imperceptibility, robustness, capacity and security. A multi-scale and secure image watermarking method is proposed in this work, which is based on the Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). Four IWT sub-bands are firstly obtained after 1-level IWT on the host image, and the corresponding singular diagonal matrices of four sub-bands can be obtained using SVD. Then, each singular diagonal matrix is divided into four non-overlapping sections in terms of the size of embedding watermark. Particularly, the size of upper left part is same as the size of watermark. The watermark can be directly embedded into four upper left parts afterwards by multiplying different scaling factors to complete the final watermarking operation. Especially, a novel optimized authentication mechanism is designed to resolve the false positive problem, which exists in the SVD-based watermarking algorithms. In addition, three-dimensional optimal mapping algorithm is proposed to search the optimal scaling factors through a novel objective evaluation function, and it can significantly improve the imperceptibility and robustness. The experimental test and comparison analysis illustrate that the proposed watermark scheme demonstrates a high imperceptibility with peak signal to noise ratio values of 45 dB and strong robustness with average normalized correlation values of 0.92.
Keyword:
Multi-scale watermarking
IWT
SVD
Optimal mapping
Authentication mechanism
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期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
3.0W
被引数:
10.2W

机构

G
Guangxi Normal University
学者数:
7.7K
论文数: 4.9K
被引数: 5.1K
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