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使用混合DWT-HMD-SVD和阿诺德编码进行增强的医疗图像水印

Himanshi Chaudhary^1,2, Preeti Garg³, Virendra P Vishwakarma⁴

¹University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, Sector 16-C, Dwarka, New Delhi, India. himanshi.c20@gmail.com.

Scientific reports

|March 21, 2025

概括

本研究介绍了一种安全的医疗图像水印技术,使用离散波纹转换 (DWT) 和单一值分解 (SVD). 该方法确保了高图像质量和强大的保护,防止常见的攻击.

科学领域:

医疗成像医学成像
数字水印是指数字水印.
信息安全信息安全

背景情况:

在数字医疗保健中,保护敏感的医疗图像免受未经授权的访问和更改至关重要.
现有的水印方法往往难以平衡不可察觉性和对各种攻击的强度.

研究的目的:

开发一个强大的和不可察觉的水印框架来保护医疗图像.
加强医疗图像数据的安全性,防止改和未经授权的访问.

主要方法:

集成离散波形变换 (DWT) 用于图像分解,赫森伯格分解 (HMD) 用于矩阵简化,奇点值分解 (SVD) 用于特征提取,以及阿诺德编码用于水印安全性.
将水印嵌入到最重要的频率子频段中,以保持图像质量.

主要成果:

达到高无感知度,峰值信号噪声比 (PSNR) 高达49dB.
对压缩和噪声加值等常见图像处理攻击表现出显著的稳定性,正常化相关性 (NC) 值高于0.9.
成功地平衡了无感知性和强度,以确保医疗图像传输的安全性.

结论:

拟议的水印框架为保护数字环境中的医疗图像提供了安全有效的解决方案.
联合使用DWT,HMD,SVD和Arnold Scrambling提供了一种可靠的方法,以确保医疗数据的完整性和机密性.

关键词:

阿诺德在乱的时候.攻击攻击攻击这就是为什么DWT DWT DWT 在NCNCNCNCNCNCNC中,我们可以看到.这是一个PSNR.水印是指水印的使用方式.

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