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Secure Image Denoising over Two Clouds

机译:在两朵云上对图像进行安全降噪

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Multimedia processing with cloud is prevalent now, which the cloud server can provide abundant resources to processing various multimedia processing tasks. However, some privacy issues must be considered in cloud computing. For a secret image, the image content should be kept secret while conducting the multimedia processing in the cloud. Multimedia processing in the encrypted domain is essential to protect the privacy in cloud computing. Hu et al. proposed a novel framework to perform complex image processing algorithms in encrypted images with two cryptosystems: additive homomorphic encryption and privacy preserving transform. The additive homomorphic cryptosystem used in their scheme causes huge ciphertext expansion and greatly increases the cloud's computation. In this paper, we modified their framework to a two-cloud scheme, and also implemented the random nonlocal means denoising algorithm. The complexity analysis and simulation results demonstrate that our new scheme is more efficient than Hu's under the same denoising performance.
机译:目前,对云的多媒体处理非常普遍,云服务器可以提供丰富的资源来处理各种多媒体处理任务。但是,在云计算中必须考虑一些隐私问题。对于秘密图像,在云中进行多媒体处理时,应将图像内容保密。加密域中的多媒体处理对于保护云计算中的隐私至关重要。 Hu等。提出了一种新颖的框架,该框架可以通过两个加密码系统在加密图像中执行复杂的图像处理算法:加性同态加密和隐私保护变换。他们的方案中使用的加性同态密码系统导致巨大的密文扩展,并大大增加了云计算。在本文中,我们将其框架修改为两云方案,并实现了随机非局部均值去噪算法。复杂度分析和仿真结果表明,在相同的去噪性能下,我们的新方案比Hu方案更有效。

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