基于冗余离散小波变换的自适应HDR图像盲水印方法

Roa'a M. Alairaji, Ibtisam A. Aljazaery, H. Alrikabi
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引用次数: 1

摘要

以保护多媒体内容的知识产权为目的的数字水印技术的应用取得了显著的成功。提出了一种新的抗色调映射攻击的高动态范围(HDR)图像零水印算法。该算法通过对HDR图像进行冗余离散小波变换(RDWT),提取稳定特征和不变特征,实现有效的零水印。第一步是将HDR图像转换为HVS色彩空间,利用v通道实现RDWT,从而获得包含图像强结构内容的LL子带。第二步,将LL子带划分为不重叠的块,然后通过奇异值分解(SVD)进行变换,从而提取U矩阵。第三,利用自回归(AR)预测技术生成局部关系模型,并进行比较,以方便生成二值特征掩模。第四步采用混合混沌映射(HCM)生成混合水印,增强了水印的安全性。最后,通过对混合水印和二元特征掩码进行异或运算,实现有效零水印的计算。基于结果,本研究中提出的方法在抵御TM攻击和其他与图像处理相关的攻击方面表现出优越的性能。
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Adaptive HDR Image Blind Watermarking Approach Based on Redundant Discrete Wavelet Transform
Remarkable success has been recorded in the usage of digital watermarking which is aimed at protecting the intellectual property of multimedia content. In this paper, a new tone mapping attack-resistant high dynamic range (HDR) image zero-watermarking algorithm is proposed. In this algorithm extraction of stable and invariant features are extracted for efficient zero-watermarking through the application of the redundant discrete wavelet transform (RDWT) to the HDR image. The first step involves transforming the HDR image to HVS color space, and RDWT is implemented using the V-channel so that the LL sub-band which contains the strong structure contents of the image is obtained. The second step involves dividing the LL sub-band into non-overlapping blocks, which are afterwards subjected to the process of transformation through the use of the singular value decomposition (SVD) so that the U matrix can be extracted. Third, the use of an Auto-Regressive (AR) prediction technique was employed in generating a local relationship model and comparison is done to facilitate the production of a binary feature mask. In the fourth process, hybrid chaotic mapping (HCM) is used to generate blended watermark so that the security of the watermark can be fortified. Lastly, the computation of an effective zero-watermark is achieved through the implementation of an exclusive-or operation on the blended watermark and the binary feature mask. Based on the results, the approach presented in this study demonstrated superior performance in terms of withstanding TM attacks and other attacks associated with image processing.
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