Performance Comparison of Watermarking Using SVD with Orthogonal Transforms and Their Wavelet Transforms
Author(s) -
H. B. Kekre,
Tanuja Sarode,
Shachi Natu
Publication year - 2015
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2015.04.01
Subject(s) - singular value decomposition , algorithm , discrete wavelet transform , mathematics , harmonic wavelet transform , singular value , wavelet transform , s transform , digital watermarking , computer science , discrete cosine transform , constant q transform , embedding , discrete sine transform , robustness (evolution) , fourier transform , wavelet , fractional fourier transform , image (mathematics) , artificial intelligence , mathematical analysis , fourier analysis , eigenvalues and eigenvectors , physics , quantum mechanics , biochemistry , chemistry , gene
A hybrid watermarking technique using Singular value Decomposition with orthogonal transforms like DCT, Haar, Walsh, Real Fourier Transform and Kekre transform is proposed in this paper. Later, SVD is combined with wavelet transforms generated from these orthogonal transforms. Singular values of watermark are embedded in middle frequency band of column/row transform of host image. Before embedding, Singular values are scaled with suitable scaling factor and are sorted. Column/row transform reduces the computational complexity to half and properties of singular value decomposition and transforms add to robustness. Behaviour of proposed method is evaluated against various attacks like compression, cropping, resizing, and noise addition. For majority of attacks wavelet transforms prove to be more robust than corresponding orthogonal transform from which it is generated.
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