基于共享矩阵和变分超先验网络的秘密图像共享方法

Yuxin Ding, Miaomiao Shao, Cai Nie
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引用次数: 0

摘要

目前,人们可以很容易地在互联网上共享多媒体信息,这导致了严重的数据安全问题。特别是在医疗、军事、金融等领域,图像总是包含着大量的敏感信息。为了保证图像在人与人之间的安全传输,人们提出了许多秘密图像共享方法。然而,现有的方法不能同时解决阴影图像的像素扩展和计算复杂度高的问题。本文提出了一种将共享矩阵与变分超先验网络相结合的图像共享方法,以减少秘密图像共享方法的像素扩展和计算复杂度。该方法采用变分超先验网络对图像进行编码。该算法引入超先验算法,有效地捕获了潜在表示中的空间依赖性,从而提高了图像压缩的效率。实验结果表明,与现有方法相比,该方法具有较低的计算复杂度和较高的安全性。此外,该方法可以有效地减少使用共享矩阵生成阴影图像时的像素扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Secret Image Sharing Method Based on Shared Matrix and Variational Hyperprior Network
At present people can easily share multimedia information on Internet, which leads to serious data security issues. Especially in medical, military and financial fields, images always contain a lot of sensitive information. To safely transmit images among people, many secret image sharing methods are proposed. However, the existing methods can not solve the problems of pixel expansion and high computational complexity of shadow images at the same time. In this paper, we propose an image sharing method by combining sharing matrix and variational hyperprior network, to reduce the pixel expansion and computational complexity of secret image sharing methods. The method uses the variational hyperprior network to encode images. It introduces the hyperprior to effectively catch spatial dependencies in the latent representation, which can compress image with high efficiency. The experimental results show that our method has low computational complexity and high security performance compared with the state-of-the-art approaches. In addition, the proposed method can effectively reduce the pixel expansion when using the sharing matrix to generate shadow images.
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