Abstract
To keep a better trade-off between robustness and imperceptibility is difficult for traditional digital watermarks. Therefore, an adaptive image watermarking method combining singular value decomposition (SVD) and the Wang–Landau (WL) sampling method is proposed to solve the problem. In this method, the third-level approximate sub-band obtained by applying the three-level wavelet transform is decomposed by SVD to obtain the principal component, which is firstly selected as the embedded position. Then, the information is finally embedded into the host image by the scaling factor. The Wang–Landau sampling method is devoted to finding the best embedding coefficient through the proposed objective evaluation function, which is a global optimization algorithm. The embedding strength is adaptively adjusted by utilizing the historical experience, which overcomes the problem of falling into local optimization easily in many traditional optimization algorithms. To affirm the reliability of the proposed method, several image processing attacks are applied and the experimental results are given in detail. Compared with other existing related watermarking techniques based on both qualitative and quantitative evaluation parameters, such as peak signal to noise ratio (PSNR) and normalized cross-correlation (NC), this method has been proven to achieve a trade-off between robustness and invisibility.
Highlights
Digital watermarking [1,2,3] technology is an important scheme to protect the security of image, audio and video and even the data collected by the Internet of Things(IoT) technology
The three-level discrete wave transformation (DWT) is used to decompose the host image to seek for the embedding position, and the watermark is embedded into the second-level approximate sub-band after singular value decomposition (SVD)
The proposed method is compared with the image watermarking methods given in [42,43,44,45], where these methods are based on the optimization algorithm, and the remaining methods used in [46,47] are not
Summary
Digital watermarking [1,2,3] technology is an important scheme to protect the security of image, audio and video and even the data collected by the Internet of Things(IoT) technology. In this paper, we proposed a global optimization scheme based on the Wang–Landau (WL) sampling method to avoid the problem of premature convergence [29] and obtained a better embedding coefficient. In this method, the scaling factor is designed as an energy value, which reflects the current state of watermarking processing using this factor. The rest of this paper is designed as follows: Section 2 introduces the preliminaries in this work; in Section 3, an adaptive image watermarking method combining SVD and Wang–Landau Sampling in the DWT domain is proposed; in Section 4, the optimization of the embedding strength factor using. WL is presented, and the experimental results are displayed and analyzed comparatively in Section 5; Section 6 puts forward the conclusion of this paper and further research works
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