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Lifting Wavelet Transform with Singular Value Decomposition for Robust Digital Image Watermarking
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 39 - Number 18 |
| Year of Publication: 2012 |
| Authors: Sushma G. Kejgir, Manesh Kokare |
10.5120/5078-7193
|
Sushma G. Kejgir, Manesh Kokare . Lifting Wavelet Transform with Singular Value Decomposition for Robust Digital Image Watermarking. International Journal of Computer Applications. 39, 18 ( February 2012), 10-18. DOI=10.5120/5078-7193
Abstract
Digital image watermarking is proposed using lifting wavelet transform and singular value decomposition for copyright protection and authentication. In this paper, lifting wavelet transform (LWT) transforms the image into subbands. The subband having energy greater than computed ‘Q’ value is selected for watermark embedding. Singular value decomposition (SVD) matrix is derived for this subband and used to embed the gray level digital signature as a watermark. This watermarking is useful for real time application since split and merge process in LWT reduces computational complexity by 50%. Loss in information is less as compared to discrete wavelet transform (DWT) algorithm, because in LWT based algorithm down and up sampling is not using. Also, use of SVD lends noninvertible property to the watermarking so that fake watermarked image cannot be generated. This algorithm is spread spectrum thus robust and semi blind needs singular values of original image for retrieval of watermark. The proposed algorithm is tested for robustness against eighteen attacks on each of the five different images. Experimental results and analysis show that proposed algorithm is trustworthy in establishing the ownership and, is robust against different attacks. Correlation coefficient (CRC) values obtained from proposed LWT-SVD algorithm are compared with DWT-SVD method.
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