DWT-SVD Based Efficient Image Watermarking Algorithm to Achieve High Robustness and Perceptual Quality

In order to improve the robustness and imperceptibleness of the algorithm, a new embedding and extracting method with DWT-SVD is proposed. The approximation matrix of the third level of image in DWT domain is modified with SVD to embed the singular value of watermark to the singular value of DWT coefficient. The proposed embedding and extracting method was employed to accelerate the hybrid DWT-SVD watermarking and to avoid the leak of watermark. This hybrid technique leads to optimize both the fundamentally conflicting requirements. The experimental results show both the good robustness under numerous attacks and the high fidelity. The time needed to perform the program is greatly decreased. Keywords— Digital watermarking, Digital signature, Discrete wavelet transform (DWT), Singular Value Decomposition (SVD), Hybrid DWT-SVD I. INTRO DUCTION In the recent few years, there is a serious problem about unauthorized and illegal access and manipulation of multimedia files over internet. Everybody can obtain copies of copyrighted multimedia openly. So we need to generate a robust method in order to protect the copy rights of media. Dig ital watermarking provides copyright protection of data. It is done by embedding additional informat ion called dig ital signature or watermark into the digital contents such that it can be detected, extracted later to ma ke an assertion about the multimedia data. [1, 2] For image watermarking, the algorithms can be categorized into one of the two domains: spatial domain or transform domain. [1, 2] In Spatial domain the data is embedded directly by modify ing pixel values of the host image, while transform domain schemes embed data by modifying transform domain coefficients. Algorithms used for special domain are less robust for various attacks as the changes are made at least Significant Substitution (LSB) of original data. While in the transform-domain the watermark is embedded by changing the magnitude of coefficients in a transform domain with the help of discrete cosine transform, discrete wavelet transform (DWT), and singular value decomposition (SVD) techniques[3, 5]. This provide most robust algorithm for many common attacks. [7] In th is paper we proposed a hybrid watermarking using DWT and SVD technique in order to achieve high robustness and transparency. This paper is organized as follows. The section2 briefly define the DWT and SVD techniques. We demonstrate the proposed approach in Section3. Here we define embedding and extract ing algorithms in DWT domain with SVD. The simulation results are illustrated in Section 4, and we also show the superiority of our scheme over the results proposed by other researchers in this section. And we conclude this paper in Section 5. II. DWT AND SVD A. Discrete Wavelet Transform(DWT) DWT involves decomposition of image into frequency channel of constant bandwidth. This causes the similarity of available decomposition at every level. DWT is implemented as mult istage transformat ion. Level wise decomposition is done in mult istage transformation. At level 1: Image is decomposed into four sub bands: LL, LH, HL, and HH where LL denotes the coarse level coefficient which is the low frequency part of the image. LH, HL, and HH denote the finest scale wavelet coefficient. The LL sub band can be decomposed further to obtain higher level of decomposition. This decomposition can continues until the desired level of decomposition is achieved for the application. The watermark can also be embedded in the remaining three sub bands to maintain the quality of image as the LL sub band is more sensitive to human eye. B. Singular Value Decomposition(SVD) An image can be represented as a matrix of positive scalar values. Formally, SVD for any image say A of size m × m is a factorization of the form g iven by A = USV , Where U and V are orthogonal matrices in which columns of U are left singular vectors and columns of V are right singular vectors of image A. S is a diagonal matrix of singular values in decreasing order. The basic idea behind SVD technique of watermarking is to find SVD of image and the altering the singular value to embed the watermark. In Dig ital watermarking schemes, SVD is used due to its main properties: 1) A s mall ag itation added in the image, does not cause large Volume 2, Issue 4, April 2012 www.ijarcsse.com © 2012, IJARCSS E All Rights Reserved Page | 76 variation in its singular values. 2) The singular value represents intrinsic algebraic image properties. [3] III. PRO POSED ALGORITHM USING DWT AND SVD TECHNIQUES A. Embedding Watermark  Use three level Haar DWT to decompose the image A in to four sub bands (i.e.,LL3 , LH3 ,HL3 , and HH3)  Apply SVD to HL3 sub band i.e., Ai = Ui SiVi T Where Ai = HL3  Apply SVD to the watermark i.e ., W = Uw SwVw T