INTRODUCTION
With the rapid development of internet and wireless networks, multimedia security and digital rights management (DRM) are becoming increasingly important issues,.Te watermarking system has been viewed as a possible solution to control unauthorized duplication and redistribution of those multimedia data. Robustness, perceptually invisibility,and security are the basic requirements for a robust watermarking system. Seeking new watermark embedding strategy to achieve performance is a very challenging problem. In this project, a proposed new blind image watermarking scheme, which is based on the multiband wavelet transform and the empirical mode decomposition.
The watermark bits can be embedded either in the spatial domain or in the transform domain, while the latter watermark embedding strategy has been demonstrated to be more robust against most of attacks. We take that latter watermarking embedding strategy in our image watermark embedding scheme, particularly we embed watermark bits indirectly in the multiband wavelet domain with the dilation factor M>2 . For M=2 , there are lots of watermarking schemes available. For instance, Prayoth et al. introduced a semi-blind watermarking scheme based on the two-band multiwavelet transform.Hsieh et al proposed a nonblind watermarking scheme based on the two-band wavelet transform and the qualified significant wavelet tree (QSWT), which is robust to JPEG compression, image cropping, median filter etc., Lahouari et al suggested a watermarking algorithm based on the balanced two-band multiwavelet transform and the well-established perceptual model, which is adaptive and highly robust.
Ng et al put forward a maximum-likelihood detection scheme that is based on modelling the distribution of the image DWT coefficients using a Laplacian probability distribution function. In Bao et al. proposed a watermarking scheme by using a quantization-index-modulation (QIM) process via wavelet domain singular value decomposition (SVD). That scheme is robust against JPEG compression but extremely sensitive to filtering and random noising.
In this project, we use the multiband wavelet domain, instead of the two-band wavelet domain, to embed the watermark bits for the reason that the multiband wavelet domain provides more capacity for watermarking and more flexible tiling of the scale-space plane. Particularly, applying the MWT with the dilation factor an image is decomposed into subimages with narrower frequency bandwidth in different scales and directions. The subimages thus generated with middle frequency are favorable blocks to embed watermark bits in our watermark embedding strategy due to the robustness against JPEG compression and various noise attacks.
For the robustness of an image watermarking system, the watermark bits are usually embedded in the perceptually significant components, mostly the low or middle frequency components of the image . he EMD, first proposed in and later demonstrated to be very useful in many areas , provides a self-adaptive decomposition of a signal, and the mean trend, the coarsest component, of the signal is highly robust under noise attack and JPEG compression. So, we select the mean trend of each subimage in the multiband wavelet domain, instead of the subimage itself, to embed the watermark bits. Our experimental results show that the watermarking based on the MWT and EMD is robust against JPEG compression, Gaussian noise, Salt and Pepper noise, median filtering and ConvFilter (Gaussian filtering and sharpening) attacks.
With the rapid development of internet and wireless networks, multimedia security and digital rights management (DRM) are becoming increasingly important issues,.Te watermarking system has been viewed as a possible solution to control unauthorized duplication and redistribution of those multimedia data. Robustness, perceptually invisibility,and security are the basic requirements for a robust watermarking system. Seeking new watermark embedding strategy to achieve performance is a very challenging problem. In this project, a proposed new blind image watermarking scheme, which is based on the multiband wavelet transform and the empirical mode decomposition.
The watermark bits can be embedded either in the spatial domain or in the transform domain, while the latter watermark embedding strategy has been demonstrated to be more robust against most of attacks. We take that latter watermarking embedding strategy in our image watermark embedding scheme, particularly we embed watermark bits indirectly in the multiband wavelet domain with the dilation factor M>2 . For M=2 , there are lots of watermarking schemes available. For instance, Prayoth et al. introduced a semi-blind watermarking scheme based on the two-band multiwavelet transform.Hsieh et al proposed a nonblind watermarking scheme based on the two-band wavelet transform and the qualified significant wavelet tree (QSWT), which is robust to JPEG compression, image cropping, median filter etc., Lahouari et al suggested a watermarking algorithm based on the balanced two-band multiwavelet transform and the well-established perceptual model, which is adaptive and highly robust.
Ng et al put forward a maximum-likelihood detection scheme that is based on modelling the distribution of the image DWT coefficients using a Laplacian probability distribution function. In Bao et al. proposed a watermarking scheme by using a quantization-index-modulation (QIM) process via wavelet domain singular value decomposition (SVD). That scheme is robust against JPEG compression but extremely sensitive to filtering and random noising.
In this project, we use the multiband wavelet domain, instead of the two-band wavelet domain, to embed the watermark bits for the reason that the multiband wavelet domain provides more capacity for watermarking and more flexible tiling of the scale-space plane. Particularly, applying the MWT with the dilation factor an image is decomposed into subimages with narrower frequency bandwidth in different scales and directions. The subimages thus generated with middle frequency are favorable blocks to embed watermark bits in our watermark embedding strategy due to the robustness against JPEG compression and various noise attacks.
For the robustness of an image watermarking system, the watermark bits are usually embedded in the perceptually significant components, mostly the low or middle frequency components of the image . he EMD, first proposed in and later demonstrated to be very useful in many areas , provides a self-adaptive decomposition of a signal, and the mean trend, the coarsest component, of the signal is highly robust under noise attack and JPEG compression. So, we select the mean trend of each subimage in the multiband wavelet domain, instead of the subimage itself, to embed the watermark bits. Our experimental results show that the watermarking based on the MWT and EMD is robust against JPEG compression, Gaussian noise, Salt and Pepper noise, median filtering and ConvFilter (Gaussian filtering and sharpening) attacks.
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