FABEMD based Innovative Watermarking Method

Eswaraiah Rayachoti, Sudhir Tirumalasetty
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Abstract

Telemedicine is overcoming obsession and is now a thriving research area. Commuting therapeutic images between distant locations is a common occurrence in telemedicine, as therapeutic images are often used by remote specialists to make inferences about diagnosis. The majority of therapeutic photographs are sent through the internet. When commuting over the internet, therapeutic photos can be attacked by various types of noise. The use of noise-affected therapeutic images may result in a misdiagnosis. As a result, the remote authority must vouch for the validity of the significant component (ROI) in the therapeutic picture and retrieve the ROI if it has been harmed by noise. This paper introduces a ground breaking watermarking method that uses Fast and Adaptive Bi-dimensional Empirical Mode Decomposition (FABEMD) to recover the ROI in a therapeutic picture when it is attacked by noise. Experiments with this novel technique have shown that the ROI in therapeutic images can be returned to its original state.
基于FABEMD的创新水印方法
远程医疗正在克服困扰,现在是一个蓬勃发展的研究领域。在远程医疗中,由于远程专家经常使用治疗图像来对诊断进行推断,因此在远程位置之间传输治疗图像是常见的情况。大多数治疗照片都是通过互联网发送的。在互联网上通勤时,治疗照片可能会受到各种噪音的攻击。使用受噪声影响的治疗图像可能导致误诊。因此,远程权威必须保证治疗图像中重要分量(ROI)的有效性,并在ROI受到噪声损害时检索它。本文介绍了一种突破性的水印方法,该方法利用快速自适应二维经验模态分解(FABEMD)来恢复治疗图像受到噪声攻击时的ROI。实验结果表明,该方法可以使治疗图像的ROI恢复到原来的状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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