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Secure Image Denoising over Two Clouds

机译:安全图像去噪超过两云

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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:具有云的多媒体处理现在是普遍的,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,应保持图像内容。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。胡等人。提出了一种新颖的框架,用于使用两个密码系统进行加密图像中的复杂图像处理算法:添加性同形加密和隐私保存变换。在其方案中使用的添加剂均匀密码系统导致巨大的密文扩展,大大增加了云的计算。在本文中,我们将其框架修改为双云方案,并且还实现了随机非局部意味着去噪算法。复杂性分析和仿真结果表明,我们的新方案比在同样的去噪表现下的效率更效率。

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