Blind image watermarking method based on linear canonical wavelet transform and QR decomposition

被引:47
作者
Guo, Yong [1 ,2 ]
Li, Bing-Zhao [1 ,2 ]
机构
[1] Beijing Inst Technol, Sch Math & Stat, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Beijing Key Lab MCAACI, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
image watermarking; wavelet transforms; blind image watermarking; linear canonical wavelet transform; QR decomposition; generalised convolution theorem; linear canonical transform; multi-resolution analysis; image representations; peak signal-to-noise ratio; geometry attacks; image processing attacks; SINGULAR-VALUE DECOMPOSITION; DOMAIN; ROBUST; SVD;
D O I
10.1049/iet-ipr.2015.0818
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Inspired by the fact that wavelet transform can be written as a classical convolution form, a new linear canonical wavelet transform (LCWT) based on generalised convolution theorem associated with linear canonical transform (LCT) is proposed recently. The LCWT not only inherits the advantages of multi-resolution analysis of wavelet transform (WT), but also has the capability of image representations in the LCT domain. Based on these good properties, the authors propose a novel image watermarking method using LCWT and QR decomposition. Compared with the existing image watermarking methods based on discrete WT or QR, this novel image watermarking method provides more flexibility in the image watermarking. Peak signal-to-noise ratio, normalised cross and structural similarity index measure are used to verify the advantages of the proposed method in simulation experiments. The experiment results show that the proposed method is not only feasible, but also robust to some geometry attacks and image processing attacks.
引用
收藏
页码:773 / 786
页数:14
相关论文
共 26 条
[1]   An optimized watermarking technique based on self-adaptive DE in DWT-SVD transform domain [J].
Ali, Musrrat ;
Ahn, Chang Wook .
SIGNAL PROCESSING, 2014, 94 :545-556
[2]  
[Anonymous], 2015, J INF HIDING MULTIME
[3]   Robust and false positive free watermarking in IWT domain using SVD and ABC [J].
Ansari, Irshad Ahmad ;
Pant, Millie ;
Ahn, Chang Wook .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2016, 49 :114-125
[4]   Image adaptive watermarking using wavelet domain singular value decomposition [J].
Bao, P ;
Ma, XH .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2005, 15 (01) :96-102
[5]   Improved wavelet-based watermarking through pixel-wise masking [J].
Barni, M ;
Bartolini, F ;
Piva, A .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (05) :783-791
[6]   Sampling and discretization of the linear canonical transform [J].
Healy, John J. ;
Sheridan, John T. .
SIGNAL PROCESSING, 2009, 89 (04) :641-648
[7]   Digital computation of linear canonical transforms [J].
Koc, Aykut ;
Ozaktas, Haldun M. ;
Candan, Cagatay ;
Kutay, M. Alper .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2008, 56 (06) :2383-2394
[8]   Blind digital watermarking method in the fractional Fourier transform domain [J].
Lang, Jun ;
Zhang, Zheng-guang .
OPTICS AND LASERS IN ENGINEERING, 2014, 53 :112-121
[9]   The Lp-dual mixed geominimal surface area for multiple star bodies [J].
Li, Yanan ;
Wang, Weidong .
JOURNAL OF INEQUALITIES AND APPLICATIONS, 2014,
[10]  
Lin C.C., 2014, J INF HIDING MULTIME, V5, P124