基于 DWT-SVD 变换和混沌图的图像鲁棒水印方法

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-05-15 DOI:10.1155/2024/6618382
Weishuai Wu, Yujiao Dong, Guangyi Wang
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引用次数: 0

摘要

现有的水印算法很难兼顾水印的隐蔽性和鲁棒性。本文提出了一种基于离散小波变换(DWT)、奇异值分解(SVD)和混沌图的鲁棒图像水印方法。该方法是一种半盲式水印方法。首先,利用广泛的混沌参数域引入了混沌逻辑帐篷图。该图与阿诺德变换相结合,对水印图像进行加密,从而提高了水印信息的安全性。随后,通过对载波图像应用 DWT,获得频域。在频域中嵌入水印可确保水印的不可见性,在对载波图像进行 DWT 处理后,优先选择高频子带,以增强水印的鲁棒性。然后将 SVD 应用于 DWT 后载波图像的高频子带和加密水印图像。最后一步是将加密水印图像的奇异值嵌入载波图像的奇异值中,从而完成水印信息嵌入过程。在模拟实验中,对各种载体图像进行了隐形测试,结果显示峰值信噪比(PSNR)一直超过 43,结构相似度(SSIM)接近 1。针对各种类型攻击的鲁棒性测试结果显示,归一化相关性(NC)值始终超过 0.9,误码率(BER)值接近 0。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Robust Watermarking Method Based on DWT-SVD Transform and Chaotic Map

The existing watermarking algorithms make it difficult to balance the invisibility and robustness of the watermark. This paper proposes a robust image watermarking method based on discrete wavelet transform (DWT), singular value decomposition (SVD), and chaotic maps. This method is a semiblind watermarking method. First, a chaotic logistic-tent map is introduced, employing an extensive chaotic parameter domain. This map is amalgamated with Arnold’s transformation to encrypt the watermark image, thereby bolstering the security of the watermark information. Subsequently, the frequency domain is obtained by applying DWT to the carrier image. Embedding watermarks in the frequency domain ensures the invisibility of the watermark, with a preference for a high-frequency subband after the DWT of the carrier image for enhanced watermark robustness. SVD is then applied to both the high-frequency subband of the carrier image after DWT and the encrypted watermark image. The final step involves embedding the singular values of the encrypted watermark image into the carrier image’s singular values, thereby completing the watermark information embedding process. In simulation experiments, an invisibility test was conducted on various carrier images, yielding peak signal-to-noise ratio (PSNR) values consistently exceeding 43, and structural similarity (SSIM) close to 1. Robustness testing against various types of attacks resulted in normalized correlation (NC) values consistently surpassing 0.9, with bit error rate (BER) values approaching 0. In conclusion, the proposed algorithm satisfies imperceptibility requirements while demonstrating formidable robustness.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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