32 research outputs found

    Imperceptible Image Watermarking based on Chinese Remainder Theorem over the Edges

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    This paper introduced a watermarking method using the CRT and Canny Algorithm that able to improve the imperceptibility of watermarked image and preserving the robustness of watermark image as well. The classical CRT algorithm is spread the watermark bits evenly on the image area. It causes significant degradation when the embedding location lies on the least significant region or in the homogeny area. Otherwise, the proposed method embeds the watermark on the edges of the image which have significant difference value to maintain the imperceptibility. The Canny algorithm is used to indexing the embedding location based on the filtering output of host image. The watermark is then embedded into the host image using pair-wise coprime integers of 6 and 11 within the CRT modulo. The results show that the proposed method has significant improvement in the quality of watermarked image with the average value of 0.9995 compared to the CRT method which results in value of 0.9985. In compression and additive noise attacks the CRT has average values of 0.6618 and 0.9750, while the proposed method results in similar values of 0.6616 and 0.9752 respectively. These prove that the proposed method is able to preserve the robustness while improving the imperceptibility

    Contourlet Domain Image Modeling and its Applications in Watermarking and Denoising

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    Statistical image modeling in sparse domain has recently attracted a great deal of research interest. Contourlet transform as a two-dimensional transform with multiscale and multi-directional properties is known to effectively capture the smooth contours and geometrical structures in images. The objective of this thesis is to study the statistical properties of the contourlet coefficients of images and develop statistically-based image denoising and watermarking schemes. Through an experimental investigation, it is first established that the distributions of the contourlet subband coefficients of natural images are significantly non-Gaussian with heavy-tails and they can be best described by the heavy-tailed statistical distributions, such as the alpha-stable family of distributions. It is shown that the univariate members of this family are capable of accurately fitting the marginal distributions of the empirical data and that the bivariate members can accurately characterize the inter-scale dependencies of the contourlet coefficients of an image. Based on the modeling results, a new method in image denoising in the contourlet domain is proposed. The Bayesian maximum a posteriori and minimum mean absolute error estimators are developed to determine the noise-free contourlet coefficients of grayscale and color images. Extensive experiments are conducted using a wide variety of images from a number of databases to evaluate the performance of the proposed image denoising scheme and to compare it with that of other existing schemes. It is shown that the proposed denoising scheme based on the alpha-stable distributions outperforms these other methods in terms of the peak signal-to-noise ratio and mean structural similarity index, as well as in terms of visual quality of the denoised images. The alpha-stable model is also used in developing new multiplicative watermark schemes for grayscale and color images. Closed-form expressions are derived for the log-likelihood-based multiplicative watermark detection algorithm for grayscale images using the univariate and bivariate Cauchy members of the alpha-stable family. A multiplicative multichannel watermark detector is also designed for color images using the multivariate Cauchy distribution. Simulation results demonstrate not only the effectiveness of the proposed image watermarking schemes in terms of the invisibility of the watermark, but also the superiority of the watermark detectors in providing detection rates higher than that of the state-of-the-art schemes even for the watermarked images undergone various kinds of attacks

    Feature Image Watermarking Based on Bicubic Interpolation of Wavelet Coefficients Using CRT

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    The main objective of watermarking method is to improve the robustness and imperceptibility. This paper introduces an improved CRT watermarking method using absolute value of interpolated wavelet coefficients aiming to improve the imperceptibility and robustness. The standard CRT method embeds the watermark bits on the blocks of pixels evenly. Hence, it can significantly reduce the quality of watermarked images when the watermark lies on the homogeneous area. Otherwise, the proposed method is embedding the watermark bits on the heterogeneous area by sorting the absolute magnitude of wavelet coefficients descending. The waveletcoefficients are selected from high frequency wavelet sub band HH. This scheme is able to determine the appropriate embedding location in certain range of value. The watermark bits are then embedding on the selectedpixel value using CRT scheme. The result shows that the average imperceptibility value the CRT is 0.9980 while the proposed method has average value of 0.9993. On robustness against compression, the proposed method achieves better result compared to the CRT with the average NC values of 0.7916 higher than the CRT value of 0.7530. These prove that the proposed method has better performance in term of imperceptibility and robustness against compression than the CRT method

    Elliptical Monogenic Wavelets for the analysis and processing of color images

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    International audienceThis paper studies and gives new algorithms for image processing based on monogenic wavelets. Existing greyscale monogenic filterbanks are reviewed and we reveal a lack of discussion about the synthesis part. The monogenic synthesis is therefore defined from the idea of wavelet modulation, and an innovative filterbank is constructed by using the Radon transform. The color extension is then investigated. First, the elliptical Fourier atom model is proposed to generalize theanalytic signal representation for vector-valued signals. Then a color Riesz-transform is defined so as to construct color elliptical monogenic wavelets. Our Radon-based monogenic filterbank can be easily extended to color according to this definition. The proposed wavelet representation provides efficient analysis of local features in terms of shape and color, thanks to the concepts of amplitude, phase, orientation, and ellipse parameters. The synthesis from local features is deeply studied. We conclude the article by defining the color local frequency, proposing an estimation algorithm

    A robust multi-watermarking algorithm for medical images based on DTCWT-DCT and Henon map

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    To resolve the contradiction between existing watermarking methods—which are not compatible with the watermark’s ability to resist geometric attacks—and robustness, a robust multi-watermarking algorithm suitable for medical images is proposed. First, the visual feature vector of the medical image was obtained by dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) to perform multi-watermark embedding and extraction. Then, the multi-watermark was pre-processed using the Henon map chaotic encryption technology to strengthen the security of watermark information, and combined with the concept of zero watermark to make the watermark able to resist both conventional and geometric attacks. Experimental results show that the proposed algorithm can effectively extract watermark information; it implements zero watermarking and blind extraction. Compared with existing watermark technology, it has good performance in terms of its robustness and resistance to geometric attacks and conventional attacks, especially in geometric attacks

    Feature Image Watermarking Based on Bicubic Interpolation of Wavelet Coefficients Using CRT

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    The main objective of watermarking method is to improve the robustness and imperceptibility. This paper introduces an improved CRT watermarking method using absolute value of interpolated wavelet coefficients aiming to improve the imperceptibility and robustness. The standard CRT method embeds the watermark bits on the blocks of pixels evenly. Hence, it can significantly reduce the quality of watermarked images when the watermark lies on the homogeneous area. Otherwise, the proposed method is embedding the watermark bits on the heterogeneous area by sorting the absolute magnitude of wavelet coefficients descending. The wavelet coefficients are selected from high frequency wavelet sub band HH. This scheme is able to determine the appropriate embedding location in certain range of value. The watermark bits are then embedding on the selected pixel value using CRT scheme. The result shows that the average imperceptibility value the CRT is 0.9980 while the proposed method has average value of 0.9993. On robustness against compression, the proposed method achieves better result compared to the CRT with the average NC values of 0.7916 higher than the CRT value of 0.7530. These prove that the proposed method has better performance in term of imperceptibility and robustness against compression than the CRT method
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