Robust Digital Watermarking Scheme using Contourlet Transform
01 Jan 2008-
TL;DR: A novel oblivious and highly robust watermarking scheme using Multiple Descriptions (MD) and Quantization Index Modulation (QIM) of the host image and superior in terms of Peak Signal to Noise Ratio (PSNR) and Normalized Cross correlation (NC).
Abstract: Summary A novel oblivious and highly robust watermarking scheme using Multiple Descriptions (MD) and Quantization Index Modulation (QIM) of the host image is presented in this paper. The watermark is embedded in the Discrete Contourlet Transform domain (CT). Discrete Countourlet Transform (CT) is able to capture the directional edges and contours superior to Discrete Wavelet Transform (DWT). Watermark embedding is done at two stages for achieving robustness to various attacks. This algorithm is highly robust for different attacks on the watermarked image and superior in terms of Peak Signal to Noise Ratio (PSNR) and Normalized Cross correlation (NC). here the part of summary.
Citations
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TL;DR: The experimental results indicate that superiority of the proposed method against common attacks such as JPEG compression, Gaussian noise addition, median filtering, salt and pepper noise, etc., compared with the existing watermarking schemes using multi-scale transformations.
Abstract: In this article, a robust blind watermarking scheme using wave atoms with multiple descriptions is proposed. In the presented scheme, the watermark image is embedded in the wave atom transform domain. One of the sub-bands is used to carry watermark data. The experimental results indicate that superiority of the proposed method against common attacks such as JPEG compression, Gaussian noise addition, median filtering, salt and pepper noise, etc., compared with the existing watermarking schemes using multi-scale transformations.
4 citations
Additional excerpts
...[19] and has been worked with DCT and contourlet transform domain [19,20]....
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TL;DR: The proposed algorithm takes advantage of a multiscale framework and multi-directionality to extract the significant frequency, luminance and texture component in an image to demonstrate the imperceptibility and the robustness against standard watermarking attacks.
Abstract: In this paper, a novel watermarking technique in contourlet transform (CT) domain is presented. The proposed algorithm takes advantage of a multiscale framework and multi-directionality to extract the significant frequency, luminance and texture component in an image. Unlike the conventional methods in the contourlet domain, mask function is accomplished pixel by pixel by taking into account the frequency, the luminance and the texture content of all the image subbands including the low-pass subband and directional subbands. The adaptive nature of the novel method allows the scheme to be adaptive in terms of the imperceptibility and robustness. The watermark is detected by computing the correlation. Finally, the experimental results demonstrate the imperceptibility and the robustness against standard watermarking attacks. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3663
4 citations
Cites background from "Robust Digital Watermarking Scheme ..."
...Meanwhile, researchers began to apply CT to the image watermarking [10-13]....
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01 Dec 2014
TL;DR: Experimental results demonstrate that the proposed image watermarking is not only invisible but also robust against a variety of attacks including scaling, rotation, flipping, noise addition, filtering, JPEG compression, etc.
Abstract: In this paper, a novel image watermarking scheme using an encrypted kinoform in the hybrid nonsubsampled contourlet transform (NSCT) and singular value decomposition (SVD) domain is presented. In the scheme, a watermark is firstly transformed into an encrypted kinoform with fractional Fourier transform and Gerchberg-Saxton algorithm. Then the host image is decomposed with NSCT and the low frequency sub-band is divided into nonoverlapping blocks. SVD is applied to every block. The kinoform is embedded into the low frequency NSCT coefficients by modifying the largest singular value of each block. To withstand geometric attacks, the geometric distortion parameters of the attacked watermarked image are computed first by the Zernike moment-based geometric correction method in the detection process. Then the mark kinoform is extracted from the recovered image. In comparison with other method, the proposed watermarking scheme offers better performances for imperceptibility. Experimental results demonstrate that the proposed image watermarking is not only invisible but also robust against a variety of attacks including scaling, rotation, flipping, noise addition, filtering, JPEG compression, etc.
4 citations
Cites background from "Robust Digital Watermarking Scheme ..."
...Many image watermarking schemes have been proposed in recent years [2-4]....
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...Even though DWT is popular, powerful, and familiar among watermarking world, it has the limitations in capturing the directional information and the directional edges of the image [4]....
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TL;DR: The experimental results reveal that the proposed watermarking scheme is robust against common image processing attacks and the results also demonstrate good imperceptibility.
Abstract: This paper presents a contourlet transform based watermarking scheme for colour images. It also makes use of discrete cosine transform and singular value decomposition. Discrete cosine transform is applied on three colour components (Y, Cb and Cr), obtained from the colour image, to produce DCT coefficients. These coefficients are decomposed into directional subbands using 2- level contourlet transform. The watermark is also decomposed using contourlet transform. The fourth directional subbands of cover image and watermark as well are further subjected to Laplacian pyramid decomposition. As a result, the low pass subbands are obtained. The singular values of lowpass subband of watermark are embedded into singular values of lowpass subband of cover image. The experimental results reveal that the proposed watermarking scheme is robust against common image processing attacks. The results also demonstrate good imperceptibility.
3 citations
Cites background from "Robust Digital Watermarking Scheme ..."
...The main feature of this transform is its efficiency in capturing two dimensional singularities like edges whereas wavelet transform capture only point singularities [7, 12]....
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Proceedings Article•
15 Feb 2009TL;DR: A novel image watermarking scheme based on Contourlet transform and singular value decomposition and adaptively applies quantization index modulation for embedding watermark according to energy distribution and human visual masking to achieve better performance in terms of perceptually invisibility and robustness of the watermark.
Abstract: In this paper, we propose a novel image watermarking scheme based on Contourlet transform and singular value decomposition. We embed watermark bits in singular value vectors of the embedded blocks within lowpass subband in Contourlet transform. We further adaptively apply quantization index modulation for embedding watermark according to energy distribution and human visual masking to achieve better performance in terms of perceptually invisibility and robustness of the watermark. The experimental results show that the proposed adaptive watermarking scheme is robust against JPEG compression, lowpass filtering, noise addition, resizing and cropping attacks. The comparison analysis demonstrates that our scheme has better performance than the watermarking schemes reported recently.
3 citations
Cites background from "Robust Digital Watermarking Scheme ..."
...Some comparisons with the watermarking schemes in [8] that is a similar approach of embedding watermark into the lowpass subband coefficients of Contourlet decomposition is also presented....
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References
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TL;DR: A "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information is pursued and it is shown that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves.
Abstract: The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. The main challenge in exploring geometry in images comes from the discrete nature of the data. Thus, unlike other approaches, such as curvelets, that first develop a transform in the continuous domain and then discretize for sampled data, our approach starts with a discrete-domain construction and then studies its convergence to an expansion in the continuous domain. Specifically, we construct a discrete-domain multiresolution and multidirection expansion using nonseparable filter banks, in much the same way that wavelets were derived from filter banks. This construction results in a flexible multiresolution, local, and directional image expansion using contour segments, and, thus, it is named the contourlet transform. The discrete contourlet transform has a fast iterated filter bank algorithm that requires an order N operations for N-pixel images. Furthermore, we establish a precise link between the developed filter bank and the associated continuous-domain contourlet expansion via a directional multiresolution analysis framework. We show that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves. Finally, we show some numerical experiments demonstrating the potential of contourlets in several image processing applications.
3,948 citations
TL;DR: A new approach to mask the watermark according to the characteristics of the human visual system (HVS) is presented, which is accomplished pixel by pixel by taking into account the texture and the luminance content of all the image subbands.
Abstract: A watermarking algorithm operating in the wavelet domain is presented. Performance improvement with respect to existing algorithms is obtained by means of a new approach to mask the watermark according to the characteristics of the human visual system (HVS). In contrast to conventional methods operating in the wavelet domain, masking is accomplished pixel by pixel by taking into account the texture and the luminance content of all the image subbands. The watermark consists of a pseudorandom sequence which is adaptively added to the largest detail bands. As usual, the watermark is detected by computing the correlation between the watermarked coefficients and the watermarking code, and the detection threshold is chosen in such a way that the knowledge of the watermark energy used in the embedding phase is not needed, thus permitting one to adapt it to the image at hand. Experimental results and comparisons with other techniques operating in the wavelet domain prove the effectiveness of the new algorithm.
949 citations
"Robust Digital Watermarking Scheme ..." refers methods in this paper
...Even though, DWT is a popular, powerful and familiar to watermarking community, it has its own limitations in capturing the directional information such as smooth contours, and directional edges of the image....
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...Image watermarking algorithms using Discrete Cosine Transform (DCT) [1, 2], Discrete Wavelet Transform (DWT) [3, 4], Discrete Hadamard Transform (DHT) [5] and Singular Value Decomposition (SVD) [6, 7] are available in the literature....
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...DWT offers multistage and time-frequency localization of the image....
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...Discrete Countourlet Transform (CT) is able to capture the directional edges and contours superior to Discrete Wavelet Transform (DWT)....
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TL;DR: The authors provide a novel mapping of the proposed 1-D framework into 2-D that preserves the following: i) perfect reconstruction; ii) stability in the IIR case; iii) linear phase in the FIR case; iv) zeros at aliasing frequency; v) frequency characteristic of the filters.
Abstract: Proposes a novel framework for a new class of two-channel biorthogonal filter banks. The framework covers two useful subclasses: i) causal stable IIR filter banks. ii) linear phase FIR filter banks. There exists a very efficient structurally perfect reconstruction implementation for such a class. Filter banks of high frequency selectivity can be achieved by using the proposed framework with low complexity. The properties of such a class are discussed in detail. The design of the analysis/synthesis systems reduces to the design of a single transfer function. Very simple design methods are given both for FIR and IIR cases. Zeros of arbitrary multiplicity at aliasing frequency can be easily imposed, for the purpose of generating wavelets with regularity property. In the IIR case, two new classes of IIR maximally flat filters different from Butterworth filters are introduced. The filter coefficients are given in closed form. The wavelet bases corresponding to the biorthogonal systems are generated. the authors also provide a novel mapping of the proposed 1-D framework into 2-D. The mapping preserves the following: i) perfect reconstruction; ii) stability in the IIR case; iii) linear phase in the FIR case; iv) zeros at aliasing frequency; v) frequency characteristic of the filters. >
417 citations
Additional excerpts
...In both LP decomposition and DFB decomposition, ‘pkva’ filters [12] are used because of their efficient implementation....
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TL;DR: In this paper, a singular value decomposition (SVD)-based watermarking scheme is proposed, which preserves both one-way and non-symmetric properties, usually not obtainable in DCT and DFT transformations.
367 citations
"Robust Digital Watermarking Scheme ..." refers methods in this paper
...Image watermarking algorithms using Discrete Cosine Transform (DCT) [1, 2], Discrete Wavelet Transform (DWT) [3, 4], Discrete Hadamard Transform (DHT) [5] and Singular Value Decomposition (SVD) [6, 7] are available in the literature....
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DOI•
01 Jan 2002
TL;DR: This thesis focuses on the development of new "true" two-dimensional representations for images using a discrete framework that can lead to algorithmic implementations and a new family of block directional and orthonormal transforms based on the ridgelet idea.
Abstract: Efficient representation of visual information lies at the foundation of many image processing tasks, including compression, filtering, and feature extraction. Efficiency of a representation refers to the ability to capture significant information of an object of interest in a small description. For practical applications, this representation has to be realized by structured transforms and fast algorithms. Recently, it has become evident that commonly used separable transforms (such as wavelets) are not necessarily best suited for images. Thus, there is a strong motivation to search for more powerful schemes that can capture the intrinsic geometrical structure of pictorial information. This thesis focuses on the development of new "true" two-dimensional representations for images. The emphasis is on the discrete framework that can lead to algorithmic implementations. The first method constructs multiresolution, local and directional image expansions by using non-separable filter banks. This discrete transform is developed in connection with the continuous-space curvelet construction in harmonic analysis. As a result, the proposed transform provides an efficient representation for two-dimensional piecewise smooth signals that resemble images. The link between the developed filter banks and the continuous-space constructions is set up in a newly defined directional multiresolution analysis. The second method constructs a new family of block directional and orthonormal transforms based on the ridgelet idea, and thus offers an efficient representation for images that are smooth away from straight edges. Finally, directional multiresolution image representations are employed together with statistical modeling, leading to powerful texture models and successful image retrieval systems.
352 citations
"Robust Digital Watermarking Scheme ..." refers methods in this paper
...In contourlet transform, DFB is implemented using quincunx filter bank with fan filters [10]....
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