Blind Image Watermark Detection Algorithm Based on Discrete Shearlet Transform Using Statistical Decision Theory

Ahmaderaghi, Baharak; Kurugöllü, Fatih; Rincón, Jesús Martínez del; Bouridane, Ahmed

doi:10.1109/tci.2018.2794065

Cited by 86 publications

(42 citation statements)

References 39 publications

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“…After wavelet analysis [3], [4], the research hotspot has always been multiscale geometric analysis (MGA), which is consistent with the sparse coding characteristics of human visual perception [5], [6]. MGA not only has multiscale and localized characteristics but also directional features and anisotropy, making it a more efficient method for sparse representation of texture and contours [7], [8]. The representative MGA methods are…”

Section: Introductionmentioning

confidence: 84%

A Novel Circular Flexible Multiscale Geometric Analysis Method

Yang

et al. 2020

IEEE Access

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Image representation is an essential problem in image processing. The most effective image representation method is multiscale geometric analysis (MGA). However, the current representative MGA method has some shortcomings, such as the fixed division of the scale spectrum and the direction spectrum, which cannot achieve well the sparsest representation of the image; the lack of rotation invariance and translation invariance make it impossible to achieve better results in the application. In this paper, a new circular flexible MGA method is proposed to solve this problem. First, the McClellan method was used to design a circular flexible multiscale decomposition, which had translation invariance and rotation invariance due to the circular spectral shape. Moreover, the spectral division of the new multiscale decomposition method could be flexibly changed according to the image, rather than being fixed at π 2 in the traditional manner. Second, new linear phase directional filter banks were proposed to divide the direction flexibly, which had selectivity in any direction. Finally, the two steps above were combined to construct a new MGA method, which maintained translation invariance, low redundancy, and flexibility in both scale and direction, resulting in better frequency localization and more sparse representation. The results of our denoising experiment show that the method proposed in this paper not only achieves a perfect reconstruction, but also performs well in image denoising compared to other state-of-the-art MGA methods. INDEX TERMS Human vision characteristic, low redundancy, multiscale geometric analysis, circular spectrum, translation and rotation invariance.

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Section: Introductionmentioning

confidence: 84%

A Novel Circular Flexible Multiscale Geometric Analysis Method

Yang

et al. 2020

IEEE Access

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“…Spatial domain algorithms usually have lower computational complexity than the transform domain watermarking algorithms. However, due to the limitations of watermarking in the spatial domain involving visualization and robustness [17], most image watermarking algorithms use the transforms such as Cosine transform [18][19][20][21][22], Fourier transform [23,24], Wavelet transform [25,26], Contourlet transform [27,28], and Shearlet transform [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

A Novel Zero-Watermarking Scheme Based on Variable Parameter Chaotic Mapping in NSPD-DCT Domain

et al. 2020

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In this paper, a novel image zero-watermarking scheme against rotation attacks is proposed based on nonsubsampled pyramid decomposition (NSPD) and discrete cosine transform (DCT). It utilizes the intrinsic characteristics of NSPD and DCT to extract the robust feature of an image as the original zero-watermark. To increase the security of the proposed scheme, a variable parameter chaotic mapping (VPCM) is designed for the processes of watermark encryption and robust feature extraction. Firstly, the host gray-scale image is decomposed by NSPD, and the low-frequency sub-band image is divided into nonoverlapping blocks. After the blocks are transformed by DCT, the signs of the first AC coefficients from all the blocks are used to construct a binary feature image. Then an exclusive-or operation is performed between the binary feature image and the encrypted watermark image to obtain the verification zero-watermark image. Furthermore, a method against arbitrary rotation attacks is employed to improve the robustness of the scheme against geometric attacks. The experimental results demonstrate that the proposed scheme is highly robust against various image processing attacks such as filtering, JPEG compression, scaling, translation, rotation and Checkmark attacks. INDEX TERMS Discrete cosine transform, Nonsubsampled pyramid decomposition, Rotation attacks, Variable parameter chaotic mapping, Zero-watermarking.

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“…Therefore, some researchers put forward the multi-scale geometric analysis methods to develop an "optimal" representation method for high-dimensional data. The multi-scale geometric analysis methods applied in digital watermarking include ridgelet transform [13,14], contourlet transform [15][16][17], bandelet transform [18], shearlet transform [19][20][21][22][23] and so on. Among them, discrete shearlet transform (DST) [24] is a new multi-scale geometric transformation proposed in 2008.…”

Section: Introductionmentioning

confidence: 99%

“…It overcomes the imperfections of limited direction selection of wavelet transform and anisotropy of base function, and has good directionality and multi-resolution representation for images. DST is widely used in image processing, and the research of digital image watermarking based on DST is gradually increasing in recent years [21][22][23]. However, most of the existing DST-based schemes have high computational complexity, which is not conducive to real-time embedding of the watermarks.…”

Section: Introductionmentioning

confidence: 99%

An entropy-based image watermarking scheme by improving robustness in shearlet and wavelet domain

Zhuang

Zhou

Liu

2020

Preprint

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The existing robust digital watermarking schemes mainly embed information in the fixed positions or with fixed embedding strength, while seldom considering adaptive adjustment based on the characteristics of the cover image, thus it reduces the imperceptibility and the robustness of watermarking. Aiming at these issues, we propose a scheme which can be able to dynamically adjust the watermark embedding position and strength. Therefore, it guarantees the trade-off between robustness and imperceptibility. The appropriate embedding positions are dynamically selected for the watermark by comparing the image entropy, and the embedding strength of the image blocks are adaptively adjusted according to the entropy and the Just Noticeable Difference (JND) model in the Human Visual System (HVS)-based wavelet domain. Singular Value Decomposition (SVD) is performed on the image blocks to ensure the resistant ability of geometric attacks. The experimental results show that the scheme has good imperceptibility as well as strong robustness against various attacks. The robustness in common attacks is improved by at least 1% compared with similar watermarking schemes.

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Blind Image Watermark Detection Algorithm Based on Discrete Shearlet Transform Using Statistical Decision Theory

Cited by 86 publications

References 39 publications

A Novel Circular Flexible Multiscale Geometric Analysis Method

A Novel Circular Flexible Multiscale Geometric Analysis Method

A Novel Zero-Watermarking Scheme Based on Variable Parameter Chaotic Mapping in NSPD-DCT Domain

An entropy-based image watermarking scheme by improving robustness in shearlet and wavelet domain

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