Content-based multipurpose watermarking for remote sensing images

Zhao, Rui; Jiang, Gangwu; Wang, Shugen

doi:10.1117/12.760809

Cited by 1 publication

(2 citation statements)

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“…Before watermarking, permutation technology is often used to disperse the error distribution to better hide watermark information. For example, Zhao et al used the total automorphism scheme to disturb the contraction and self‐correlation of the watermarked image . Zhou et al proposed a logistic map to change the image into a disordered state .…”

Section: Methodsmentioning

confidence: 99%

“…For example, Zhao et al used the total automorphism scheme to disturb the contraction and selfcorrelation of the watermarked image. 35 Zhou et al proposed a logistic map to change the image into a disordered state. 36 Of the currently available permutation methods, the Arnold permutation is simple and easy to implement and has been widely used in watermark research; therefore, it is adopted in this paper.…”

Section: Watermark Preprocessingmentioning

confidence: 99%

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Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

Che

Luo

et al. 2019

Math Methods in App Sciences

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Digital watermarking is important for protecting the intellectual property of remote sensing images. Unlike watermarking in ordinary colour images, in colour remote sensing images, watermarking has an important requirement: robustness. In this paper, a robust nonblind watermarking scheme for colour remote sensing images, which considers both frequency and statistical pattern features, is constructed based on the quaternion wavelet transform (QWT) and tensor decomposition. Using the QWT, not only the abundant phase information can be used to preserve detailed host image features to improve the imperceptibility of the watermark, but also the frequency coefficients of the host image can provide a stable position to embed the watermark. To further strengthen the robustness, the global statistical feature structure acquired through the tensor Tucker decomposition is employed to distribute the watermark's energy among different colour bands. Because both the QWT frequency coefficients and the tensor decomposition global statistical feature structure are highly stable against external distortion, their integration yields the proposed scheme, which is robust to many image manipulations. A simulation experiment shows that our method can balance the trade‐off between imperceptibility and robustness and that it is more robust than the traditional QWT and discrete wavelet transform (DWT) methods under many different types of image manipulations.

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Section: Methodsmentioning

confidence: 99%

Section: Watermark Preprocessingmentioning

confidence: 99%