Suppr超能文献

基于 Hadamard 变换和分数阶矩的彩色医学图像盲水印

Blind Watermarking of Color Medical Images Using Hadamard Transform and Fractional-Order Moments.

机构信息

Department of Information Technology, Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt.

Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID 83209, USA.

出版信息

Sensors (Basel). 2021 Nov 25;21(23):7845. doi: 10.3390/s21237845.

Abstract

This paper proposes a new blind, color image watermarking method using fast Walsh-Hadamard transformation (FWHT) and multi-channel fractional Legendre-Fourier moments (MFrLFMs). The input host color image is first split into 4 × 4 non-interfering blocks, and the MFrLFMs are computed for each block, where proper MFrLFMs coefficients are selected and FWHT is applied on the selected coefficients. The scrambled binary watermark has been inserted in the quantized selected MFrLFMs coefficients. The proposed method is a blind extraction, as the original host image is not required to extract the watermark. The proposed method is evaluated over many visual imperceptibility terms such as peak signal-to-noise ratio (PSNR), normalized correlation (NC), and bit error rate. The robustness of the proposed method is tested over several geometrical attacks such as scaling, rotation, cropping, and translation with different parameter values. The most widely recognized image processing attacks are also considered, e.g., compressing and adding noise attacks. A set of combination attacks are also tested to analyze the robustness of the proposed scheme versus several attacks. The proposed model's experimental and numerical results for invisibility and robustness were superior to the results of similar watermarking methods.

摘要

本文提出了一种新的基于快速沃尔什-哈达玛变换(FWHT)和多通道分数阶勒让德-傅里叶矩(MFrLFMs)的盲彩色图像水印方法。输入的彩色宿主图像首先被分成 4×4 个非干扰块,并对每个块计算 MFrLFMs,其中选择合适的 MFrLFMs 系数并对所选系数应用 FWHT。已将置乱的二进制水印插入量化后的所选 MFrLFMs 系数中。该方法是一种盲提取方法,因为不需要原始宿主图像来提取水印。该方法通过许多视觉不可感知性指标进行评估,例如峰值信噪比(PSNR)、归一化相关(NC)和误码率。该方法还针对多种几何攻击进行了稳健性测试,例如缩放、旋转、裁剪和不同参数值的平移。还考虑了最广泛认可的图像处理攻击,例如压缩和添加噪声攻击。还测试了一组组合攻击,以分析该方案对多种攻击的稳健性。与类似的水印方法相比,该模型的实验和数值结果在不可见性和稳健性方面都更优。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd57/8659669/bb1bf9ec37d4/sensors-21-07845-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验