用于认证数据保护的混合域水印方法

N. Radha, K. Meenakshi
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引用次数: 0

摘要

图像水印已发展成为数据保护领域的一个重要研究领域。通过互联网传输的认证数据并不安全,可能被未经授权的人盗用。为了保护有效数据,在混合域中提出了基于静态小波变换(SWT)、离散小波变换(DWT)和奇异值分解(SVD)的图像水印算法。首先,使用 SWT 将原始图像和水印图像分解为近似子带 (A)、垂直子带 (V)、水平子带 (H) 和对角线子带 (D)。近似带 (A) 使用 DWT 进一步分解为 LL 和细节(LH、HL 和 HH)子带。我们对原始图像和水印图像的 LL 和 HH 子带进行 SVD 计算,以获得奇异值。对 LL 和 HH 子带的奇异值进行修改,得到水印图像。在标准图像数据集上测试了所提议模型的性能。使用峰值信噪比 (PSNR)、结构相似性指数 (SSIM) 和特征相似性指数 (FSIM) 指标对不可感知性进行了评估,并根据归一化交叉相关性 (NCC) 从受攻击的水印图像中有效提取水印的情况验证了鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Hybrid domain watermarking approach for authenticated data protection

Hybrid domain watermarking approach for authenticated data protection

Image watermarking has developed as a prominent research area in the field of data protection. The authenticated data transmitted through the internet is not secure and can be pirated by unauthorized persons. To protect the valid data, Stationary Wavelet Transform (SWT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) based image watermarking algorithm is proposed in the hybrid domain. Initially the original and watermark images are decomposed into approximate (A), vertical (V), horizontal (H), and diagonal subbands (D) using SWT. The approximate band (A) is further decomposed into LL and detail (LH, HL, and HH) subbands using DWT. We calculated SVD for LL and HH subbands of original and watermark images to get the singular values. The singular values of the LL and HH subbands are modified to get the watermarked image. The performance of the proposed model is tested on a standard image dataset. The imperceptibility is evaluated using Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Feature Similarity Index (FSIM) metrics, and the robustness is validated based on the effective extraction of watermarks from the attacked watermarked image in terms of Normalized Cross Correlation (NCC).

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