Open AccessBlind image watermarking method based on linear canonical wavelet transform and QR decomposition
Author(s) -
Guo Yong,
Li BingZhao
Publication year - 2016
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2015.0818
Subject(s) - convolution (computer science) , digital watermarking , stationary wavelet transform , second generation wavelet transform , mathematics , wavelet transform , discrete wavelet transform , wavelet , algorithm , harmonic wavelet transform , wavelet packet decomposition , artificial intelligence , peak signal to noise ratio , pattern recognition (psychology) , image (mathematics) , computer science , artificial neural network
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.